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\def\makelabel##1{\upshape ##1}}% } {\end{list}\end{raggedright}} \newenvironment{specHead}[2]% {\vspace{20pt}\hrule\vspace{10pt}% \phantomsection\label{#1}\markright{#2}% \pdfbookmark[2]{#2}{#1}% \hspace{-0.75in}{\bfseries\fontsize{16pt}{18pt}\selectfont#2}% }{} \def\TheFullDate{2017 2017-01-15 (revised: 16 Year 2017 15 January 2017)} \def\TheID{\makeatother } \def\TheDate{2017 2017-01-15} \title{Alpha Trimmed Mean based JPEG Compression for an Objective Image Quality Enhancement of Noisy and Noise Less Images} \author{}\makeatletter \makeatletter \newcommand*{\cleartoleftpage}{% \clearpage \if@twoside \ifodd\c@page \hbox{}\newpage \if@twocolumn \hbox{}\newpage \fi \fi \fi } \makeatother \makeatletter \thispagestyle{empty} \markright{\@title}\markboth{\@title}{\@author} \renewcommand\small{\@setfontsize\small{9pt}{11pt}\abovedisplayskip 8.5\p@ plus3\p@ minus4\p@ \belowdisplayskip \abovedisplayskip \abovedisplayshortskip \z@ plus2\p@ \belowdisplayshortskip 4\p@ plus2\p@ minus2\p@ \def\@listi{\leftmargin\leftmargini \topsep 2\p@ plus1\p@ minus1\p@ \parsep 2\p@ plus\p@ minus\p@ \itemsep 1pt} } \makeatother \fvset{frame=single,numberblanklines=false,xleftmargin=5mm,xrightmargin=5mm} \fancyhf{} \setlength{\headheight}{14pt} \fancyhead[LE]{\bfseries\leftmark} \fancyhead[RO]{\bfseries\rightmark} \fancyfoot[RO]{} \fancyfoot[CO]{\thepage} \fancyfoot[LO]{\TheID} \fancyfoot[LE]{} \fancyfoot[CE]{\thepage} \fancyfoot[RE]{\TheID} \hypersetup{citebordercolor=0.75 0.75 0.75,linkbordercolor=0.75 0.75 0.75,urlbordercolor=0.75 0.75 0.75,bookmarksnumbered=true} \fancypagestyle{plain}{\fancyhead{}\renewcommand{\headrulewidth}{0pt}} \date{} \usepackage{authblk} \providecommand{\keywords}[1] { \footnotesize \textbf{\textit{Index terms---}} #1 } \usepackage{graphicx,xcolor} \definecolor{GJBlue}{HTML}{273B81} \definecolor{GJLightBlue}{HTML}{0A9DD9} \definecolor{GJMediumGrey}{HTML}{6D6E70} \definecolor{GJLightGrey}{HTML}{929497} \renewenvironment{abstract}{% \setlength{\parindent}{0pt}\raggedright \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt \textcolor{GJBlue}{\large\bfseries\abstractname\space} }{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{Vanitha Kakollu} \author[2]{P. Chandrasekhar Reddy} \affil[1]{ GITAM INSTITUTE OF SCIENCE} \renewcommand\Authands{ and } \date{\small \em Received: 7 December 2016 Accepted: 4 January 2017 Published: 15 January 2017} \maketitle \begin{abstract} We can see that over the past few years, the number of people using internet and the amount of information that is being transmitted over the internet has grown to such a wide range. One of the best ways to reduce the image size is via image compression. In the compression of still image, JPEG is better when it comes to bandwidth conservation. In this paper, we discussed an innovative JPEG compression algorithm with alpha trimmed means based clustering. The proposed algorithm is expected to produce better results in terms of MSE, PSNR and number of bits transmitted, when compared to the standard algorithms. The proposed JPEG algorithm enhances the speed and reduces the number of encoded bits, thereby reducing the amount of memory required. The reassembled image after decompression is as similar as the input image. \end{abstract} \keywords{image compression, clustering, PSNR, MSE, AD, SC.} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{I. Introduction}]{I. Introduction}\par he encoder generates a set of symbols when a two-dimensional image f(x, y) is given as an input. Then transmit this through a channel and the encoded image is now sent to the decoder. The decoder generates a reconstructed image f'(x, y). The output f'(x, y) is an accurate imitation of f(x, y) in lossless compression. Else it means that there is some misconception present in the re-enacted image \hyperref[b0]{[1]}.\par The JPEG (Joint Photographic Experts Group), the committee that shaped the JPEG standard, is an identifiable lossy compression proposal. Not just using less memory, but also the data in the regenerated image in a JPEG compression appears very much identical. Though the quality is reduced with JPEG compression, the image will look nearly as similar as the original image.\par The JPEG Algorithm wipes out high-frequency components that the human eye can't identify. \section[{a) JPEG Algorithm}]{a) JPEG Algorithm}\par When compared to straight better, it involves the following steps. 1. The acquired image can be divided it into 8-pixel by 8-pixel blocks. If the image size is not precisely multiplied by 8, then add zeros in empty pixels around the edges. \hyperref[b0]{[1]}.\par If in 8x8 blocks include a lot of dissimilarity in pixel values then the number of constructive DCT coefficients will grow to be more. Otherwise only first few DCT coefficients will be more noteworthy while others are zeros. On the application of filters, as a result the image gets smoothened the distinction of the pixel values of a block abridged \hyperref[b0]{[1]}. \section[{II. Intended Innovative JPEG Compression Algorithms}]{II. Intended Innovative JPEG Compression Algorithms}\par If in 8x8 blocks include lot of distinction in pixel values then the number of constructive DCT coefficients will grow to be more. Otherwise only first few DCT coefficients will be more noteworthy while others are zeros. On the application of filters the image gets smoothened as a result the distinction of the pixel values of a block abridged.\par There are two different ways to implement the JPEG Algorithm. 1) Earlier than segregating the image into 8X8 blocks the images tainted with Poisson, Speckle, Salt \& Pepper noise and Gaussian noise is convoluted with Alpha trimmed Mean filter.\par 2) Before the application of normalized matrix, the image is convoluted with the Alpha trimmed Mean filter. This paper examines the comparison between the proposed approaches with the standard JPEG compression. The planned methods illustrate enhanced results compared to the JPEG in terms encoded bits. This paper implements the proposed algorithms by using MATLAB tools and the images are extracted from SIPI image database. Algorithm1: Alpha trimmed Mean Based JPEG algorithm on noisy images. Step1: Read the image.\par Step 2: Apply the smoothening operator Alpha trimmed Mean.\par Step 3: Standard Jpeg Compression \hyperref[b7]{[7,}\hyperref[b8]{8,}\hyperref[b9]{9]}. \section[{III. Implementation of Planned JPEG Algorithms}]{III. Implementation of Planned JPEG Algorithms}\par In this paper Alpha trimmed mean based JPEG compression is executed on images of different sizes. Contemplation of results entrusts that the lately expected compression techniques are enormously a prominent alternate since they are proved to be better regarding image quality metrics like PSNR, MSE, AD, SC, Compression ratio.\par N1 is the extent of information hauling units required to imply uncompressed dataset and N2 is the number of entities in the encoded dataset. The units for N1 and N2 are same. Step1: Read the image. \section[{CR = N1/N2}]{CR = N1/N2}\par Step 2: Apply speckle/Poisson/ Gaussian/ Salt \& Pepper Noise.\par Step 3: Apply Alpha trimmed Mean.\par Step 4: Standard Jpeg Compression \hyperref[b8]{[8,}\hyperref[b9]{9]}.\par The reconstructed image is identical to the original image with lossless compression algorithms as they not only swab out redundancy but also eradicates the redundancy present in the data they even guard all the information that is present in the input image.\par Higher compression is achieved in lossy compression algorithms as the output image and the input image will not be similar. We can either use subjective fidelity criteria or objective fidelity criteria for comparing the original and reprocessed image. An example for objective fidelity criteria is Root mean square (RMS) error.\par Measurement of the image quality is an imperative implication in image processing. In many of the image processing applications, estimation is a compulsion for the excellence of the image. The judgment of the quality of an image by the human is not sufficient. Therefore some more metrics like PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) are needed. PSNR is one of the specialized image quality metric. The differences between the restructured image and the input image will be small when the PSNR value is high.\par This paper spot the comparison between the proposed Alpha trimmed Mean based approaches with the standard JPEG compression. The premeditated approaches exemplify improved results contrasted to the JPEG. Out of these proposed JPEG compressions the Alpha Trimmed Mean filter on images corrupted with on Poisson noise in algorithm1, Alpha trimmed Mean on images encodes the images with a fewer number of bits, as a result the images will be transmitted with high speed. The decisive insinuation in image processing is the amount of image quality. Evaluation and assessing are obligatory for image quality in many image processing implementations. The refinement of human to boost the image quality is not adequate. So we necessitate some additional image quality metrics like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR).\par The number of encoded bits required to characterize the compressed image is minimized with the Alpha trimmed Mean. The corrupted images with Poisson noise in the proposed algorithm resulted a high compression ratio compared to the standard JPEG compression technique. \section[{IV. Results}]{IV. Results}\par This paper presents the evaluation between the proposed Alpha trimmed mean based JPEG approaches with the standard JPEG compression. The wished-for approaches typify improved results compared to the JPEG. This paper makes use of MATLAB tools to access the proposed algorithm and the images are from SIPI image database. \section[{Conclusion}]{Conclusion}\par In this paper, Alpha trimmed mean based JPEG compression algorithm is proposed. This algorithm is evaluated with standard JPEG algorithm. The proposed algorithm uses less encoded bits for compression of images and hence the loading and storing of the image took less time. Also, the mean square error (MSE) of the proposed approach is low compared to the regular classification correctness is augmented with the estimated approach. The projected compression ratio can be realized with good quality image with necessary planned algorithm compared to JPEG compression technique. The requirement of encoded bits to represent the compressed image is less compared to JPEG compression. Also the image corrupted with various types of noises like Gaussian, Poisson, Speckle, Salt \& Pepper noise are compressed efficiently with alpha trimmed JPEG compression. This proposed alpha trimmed JPEG compression algorithm eliminates the noise and encodes the image with fewer number of bits compared JPEG compression technique. JPEG. Due to the peak signal noise ratio (PSNR) perfect \begin{figure}[htbp] \noindent\textbf{12}\includegraphics[]{image-2.png} \caption{\label{fig_0}Fig. 1 :Algorithm 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{2}\includegraphics[]{image-3.png} \caption{\label{fig_1}Fig. 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{12456873}\includegraphics[]{image-4.png} \caption{\label{fig_2}Fig. 1 :Fig. 2 :Fig. 4 :Fig. 5 :Fig. 6 :Fig . 8 :Fig. 7 :Fig. 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{} \end{longtable} \par {\small\itshape [Note: frequency components. Next, the assortment of significant 2-D normalized DCT Coefficients by traversing in a ZIGZAG fashion and categorizing them in a 1-D array. In the 1-D array, the two types of DCT coefficients the first one is termed as direct current (DC) element, while other coefficients are called alternating current (AC) elements. Variable length Huffman coding is used to code AC components. 6. The reverse operation of compression is decompression. First calculate the normalized DCT values by decoding the compressed bit stream by Huffman code. Then organize all the DCT values in the 2-D array in a ZIGZAG fashion. We can obtain the decoded DCT values by multiplying them with normalized coefficients. Now an IDCT is executed on the denormalized DCT array. The decoding process engenders ensuing image block will not be identical to respective original image block used during encoding]} \caption{\label{tab_0}}\end{figure} \begin{figure}[htbp] \noindent\textbf{1} \par \begin{longtable}{P{0.4530562347188264\textwidth}P{0.15378973105134475\textwidth}P{0.07481662591687041\textwidth}P{0.0852078239608802\textwidth}P{0.08312958435207825\textwidth}} No of Bits Required\tabcellsep \multicolumn{2}{l}{38915 35567}\tabcellsep 40756\tabcellsep 48505\\ \multicolumn{5}{l}{Saved bits 485373 488721 483532 475483}\\ RMS Error\tabcellsep 1.99\tabcellsep 2.14\tabcellsep 2.16\tabcellsep 2.95\\ Compression ratio\tabcellsep 13.47\tabcellsep 14.74\tabcellsep 12.86\tabcellsep 10.8\\ PSNR\tabcellsep 42.19\tabcellsep 41.55\tabcellsep 41.48\tabcellsep 38.76\\ MSE\tabcellsep 3.96\tabcellsep 4.58\tabcellsep 4.66\tabcellsep 8.71\\ Images\tabcellsep \multicolumn{4}{l}{5.2.08 5.2.10 7.1.03 7.1.05}\\ \multicolumn{5}{l}{No of Bits Required 160880 185945 151629 171235}\\ \multicolumn{5}{l}{Saved bits 1936272 1911207 1945523 1925917}\\ RMS Error\tabcellsep 1.98\tabcellsep 2.15\tabcellsep 1.92\tabcellsep 1.97\\ Compre ssion\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ ratio\tabcellsep 13.03\tabcellsep 11.27\tabcellsep 13.83\tabcellsep 12.24\\ PSNR\tabcellsep 48.27\tabcellsep 47.54\tabcellsep 48.52\tabcellsep 48.30\\ MSE\tabcellsep 3.91\tabcellsep 4.61\tabcellsep 3.68\tabcellsep 3.88\end{longtable} \par {\small\itshape [Note: © 2017 Global Journals Inc. (US)]} \caption{\label{tab_2}Table 1 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{2} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_3}Table 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{3} \par \begin{longtable}{P{0.24846153846153846\textwidth}P{0.21794871794871792\textwidth}P{0.18743589743589742\textwidth}P{0.10025641025641026\textwidth}P{0.09589743589743589\textwidth}} \multicolumn{2}{l}{Images 5.1.09}\tabcellsep \multicolumn{3}{l}{5.1.11 5.1.12 5.1.13}\\ No of\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Bits Required\tabcellsep 33233\tabcellsep 32096\tabcellsep 37968\tabcellsep 52879\\ Saved bits\tabcellsep \multicolumn{4}{l}{491055 492192 486320 471409}\\ RMS Error\tabcellsep 1.62\tabcellsep 2.21\tabcellsep 1.96\tabcellsep 2.66\\ \tabcellsep 15.77\tabcellsep 16.33\tabcellsep 13.80\tabcellsep 9.91\\ PSNR\tabcellsep 43.95\tabcellsep 41.28\tabcellsep 42.30\tabcellsep 39.67\\ MSE\tabcellsep 2.64\tabcellsep 4.88\tabcellsep 3.86\tabcellsep 7.07\end{longtable} \par \caption{\label{tab_4}Table 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{4} \par \begin{longtable}{P{0.16210474308300396\textwidth}P{0.12514822134387352\textwidth}P{0.06635375494071145\textwidth}P{0.08231225296442687\textwidth}P{0.07139328063241107\textwidth}P{0.08483201581027669\textwidth}P{0.13522727272727272\textwidth}P{0.03023715415019763\textwidth}P{0.04619565217391304\textwidth}P{0.04619565217391304\textwidth}} \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Images\tabcellsep \multicolumn{2}{l}{5.1.09 5.1.11}\tabcellsep 5.1.12\tabcellsep 5.1.13\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep No of\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Bits\tabcellsep \multicolumn{4}{l}{131762 128052 130105 112493}\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Required\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Saved bits\tabcellsep \multicolumn{4}{l}{392526 396236 394183 411795}\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep RMS Error\tabcellsep 8.30\tabcellsep 8.21\tabcellsep 8.14\tabcellsep 7.18\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 3.97\tabcellsep 4.09\tabcellsep 4.02\tabcellsep 4.66\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep PSNR\tabcellsep 29.79\tabcellsep 29.88\tabcellsep 29.95\tabcellsep 31.04\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep MSE\tabcellsep 68.84\tabcellsep 67.39\tabcellsep 66.25\tabcellsep 51.56\\ Images\tabcellsep \multicolumn{2}{l}{5.2.08 5.2.10}\tabcellsep 7.1.03\tabcellsep 7.1.05\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ No of Bits Required\tabcellsep \multicolumn{2}{l}{134461 170584}\tabcellsep \multicolumn{2}{l}{124837 151040}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Saved bits RMS Error\tabcellsep \multicolumn{4}{l}{196261 1926568 1972315 1946112 1.55 1.78 1.46 1.54}\tabcellsep Images No of Required Bits\tabcellsep \multicolumn{2}{l}{5.2.08 5.2.10 534501 571916}\tabcellsep 7.1.03 523400\tabcellsep 7.1.05 543731\\ \tabcellsep 15.59\tabcellsep 12.29\tabcellsep 16.79\tabcellsep 13.88\tabcellsep Saved bits\tabcellsep \multicolumn{4}{l}{1562651 1525236 1573752 1553421}\\ PSNR\tabcellsep 50.37\tabcellsep 49.17\tabcellsep 50.87\tabcellsep 50.45\tabcellsep RMS Error\tabcellsep 8.24\tabcellsep 8.22\tabcellsep 8.28\tabcellsep 8.29\\ MSE\tabcellsep 2.41\tabcellsep 3.17\tabcellsep 2.14\tabcellsep 2.37\tabcellsep \tabcellsep 3.92\tabcellsep 3.66\tabcellsep 4.00\tabcellsep 3.85\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep PSNR\tabcellsep 35.86\tabcellsep 35.89\tabcellsep 35.82\tabcellsep 35.82\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep MSE\tabcellsep 67.97\tabcellsep 67.49\tabcellsep 68.57\tabcellsep 68.64\\ Images\tabcellsep 5.1.09\tabcellsep 5.1.11\tabcellsep 5.1.12\tabcellsep 5.1.13\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ No of Bits Required\tabcellsep 32309\tabcellsep 27980\tabcellsep 34650\tabcellsep 46407\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Saved bits\tabcellsep 492249\tabcellsep 496308\tabcellsep 489638\tabcellsep 477881\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ RMS Error\tabcellsep 1.56\tabcellsep 1.82\tabcellsep 1.92\tabcellsep 2.46\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep 16.36\tabcellsep 18.73\tabcellsep 15.13\tabcellsep 11.29\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ PSNR\tabcellsep 44.33\tabcellsep 42.96\tabcellsep 42.50\tabcellsep 40.35\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ MSE\tabcellsep 2.42\tabcellsep 3.31\tabcellsep 3.69\tabcellsep 6.04\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{2}{l}{Images 5.2.08}\tabcellsep 5.2.10\tabcellsep 7.1.03\tabcellsep 7.1.05\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ No of Bits Required\tabcellsep 134490\tabcellsep 170840\tabcellsep 124478\tabcellsep 150890\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{Saved bits 1962662 1926312 1972674 1946262}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ RMS Error\tabcellsep 1.53\tabcellsep 1.82\tabcellsep 1.46\tabcellsep 1.54\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep 15.59\tabcellsep 12.27\tabcellsep 16.84\tabcellsep 13.89\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ PSNR\tabcellsep 50.52\tabcellsep 49.00\tabcellsep 50.90\tabcellsep 50.44\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ MSE\tabcellsep 2.33\tabcellsep 3.30\tabcellsep 2.13\tabcellsep 2.37\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_5}Table 4 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{5} \par \begin{longtable}{P{0.4349765258215962\textwidth}P{0.09178403755868544\textwidth}P{0.09178403755868544\textwidth}P{0.11572769953051643\textwidth}P{0.11572769953051643\textwidth}} \multicolumn{3}{l}{Images 5.1.09 5.1.11}\tabcellsep 5.1.12\tabcellsep 5.1.13\\ No of Bits Required\tabcellsep 31807\tabcellsep 28385\tabcellsep 34746\tabcellsep 46210\\ \multicolumn{5}{l}{Saved bits 492481 495903 489542 478078}\\ RMS Error\tabcellsep 1.56\tabcellsep 1.86\tabcellsep 1.86\tabcellsep 2.49\\ Compression\tabcellsep 16.48\tabcellsep 18.47\tabcellsep 15.08\tabcellsep 11.34\\ ratio\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ PSNR\tabcellsep 44.28\tabcellsep 42.76\tabcellsep 42.78\tabcellsep 40.22\\ MSE\tabcellsep 2.44\tabcellsep 3.47\tabcellsep 3.46\tabcellsep 6.22\end{longtable} \par \caption{\label{tab_6}Table 5 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{6} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_7}Table 6 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{7} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_8}Table 7 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{8} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_9}Table 8 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{9} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_10}Table 9 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{10} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_11}Table 10 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{11} \par \begin{longtable}{P{0.46213592233009704\textwidth}P{0.08252427184466019\textwidth}P{0.27233009708737865\textwidth}P{0.033009708737864074\textwidth}} \multicolumn{2}{l}{C}\tabcellsep ompression\\ \tabcellsep \tabcellsep atio r\\ ompression C\tabcellsep \\ ratio\tabcellsep \\ \multicolumn{2}{l}{C}\tabcellsep ompression\\ \tabcellsep \tabcellsep atio r\\ ompression C\tabcellsep \\ atio r\tabcellsep \\ C\tabcellsep \multicolumn{2}{l}{ompression}\\ \tabcellsep \tabcellsep r\tabcellsep atio\\ ompression C\tabcellsep \\ atio r\tabcellsep \end{longtable} \par \caption{\label{tab_12}Table 11 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{17} \par \begin{longtable}{P{0.22272727272727272\textwidth}P{0.1590909090909091\textwidth}P{0.15454545454545454\textwidth}P{0.1590909090909091\textwidth}P{0.15454545454545454\textwidth}} Images\tabcellsep 5.1.09\tabcellsep 5.1.11\tabcellsep 5.1.12\tabcellsep 5.1.13\\ No of\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Bits\tabcellsep 29370\tabcellsep 22971\tabcellsep 30094\tabcellsep 45560\\ Required\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Saved bits\tabcellsep 494918\tabcellsep 501317\tabcellsep 494194\tabcellsep 478728\\ RMS Error\tabcellsep 1.35\tabcellsep 1.68\tabcellsep 1.48\tabcellsep 2.17\\ \tabcellsep 17.85\tabcellsep 22.8\tabcellsep 17.42\tabcellsep 11.5\\ PSNR\tabcellsep 45.58\tabcellsep 43.68\tabcellsep 44.78\tabcellsep 41.44\\ MSE\tabcellsep 1.81\tabcellsep 2.81\tabcellsep 2.18\tabcellsep 4.71\end{longtable} \par \caption{\label{tab_13}Table 17 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{12} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_14}Table 12 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{13} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_15}Table 13 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{14} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_16}Table 14 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{15} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_17}Table 15 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{16} \par \begin{longtable}{P{0.032692307692307694\textwidth}P{0.29423076923076924\textwidth}P{0.3596153846153846\textwidth}P{0.16346153846153846\textwidth}} C\tabcellsep \multicolumn{2}{l}{ompression atio r}\\ \tabcellsep \multicolumn{2}{l}{C}\tabcellsep ompression\\ \tabcellsep \tabcellsep atio r\\ \multicolumn{2}{l}{C}\tabcellsep ompression\\ \tabcellsep \tabcellsep atio r\end{longtable} \par \caption{\label{tab_18}Table 16 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{18} \par \begin{longtable}{P{0.27557077625570775\textwidth}P{0.18630136986301368\textwidth}P{0.14166666666666666\textwidth}P{0.12420091324200912\textwidth}P{0.12226027397260272\textwidth}} Images\tabcellsep 5.2.08\tabcellsep 5.2.10\tabcellsep 7.1.03\tabcellsep 7.1.05\\ No of\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Bits\tabcellsep 126602\tabcellsep 168049\tabcellsep 115194\tabcellsep 147353\\ Required\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Saved bits\tabcellsep \multicolumn{4}{l}{1970550 1929103 1981958 1949799}\\ RMS Error\tabcellsep 1.35\tabcellsep 1.74\tabcellsep 1.29\tabcellsep 1.43\\ \tabcellsep 16.56\tabcellsep 12.47\tabcellsep 18.2\tabcellsep 14.23\\ PSNR\tabcellsep 51.57\tabcellsep 49.37\tabcellsep 51.97\tabcellsep 51.05\\ MSE\tabcellsep 1.83\tabcellsep 3.03\tabcellsep 1.67\tabcellsep 2.06\\ \multicolumn{5}{l}{Table 19: JPEG Compression on Images of size}\\ \tabcellsep \tabcellsep 256X256.\tabcellsep \tabcellsep \\ Images\tabcellsep 5.1.09\tabcellsep 5.1.11\tabcellsep 5.1.12\tabcellsep 5.1.13\\ No of\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Bits\tabcellsep 60840\tabcellsep 40534\tabcellsep 50289\tabcellsep 65622\\ Required\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Saved bits\tabcellsep 463448\tabcellsep 483754\tabcellsep 473999\tabcellsep 458666\\ RMS Error\tabcellsep 4.25\tabcellsep 2.26\tabcellsep 3.04\tabcellsep 3.6\\ \tabcellsep 8.61\tabcellsep 12.93\tabcellsep 10.42\tabcellsep 7.98\\ PSNR\tabcellsep 35.59\tabcellsep 41.10\tabcellsep 38.50\tabcellsep 37.5\\ MSE\tabcellsep 18.10\tabcellsep 5.09\tabcellsep 9.26\tabcellsep 12.94\end{longtable} \par \caption{\label{tab_19}Table 18 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{20} \par \begin{longtable}{P{0.2072139303482587\textwidth}P{0.25796019900497513\textwidth}P{0.19029850746268656\textwidth}P{0.09726368159203981\textwidth}P{0.09726368159203981\textwidth}} Images\tabcellsep 5.2.08\tabcellsep 5.2.10\tabcellsep 7.1.03\tabcellsep 7.1.05\\ No of\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Bits\tabcellsep 246431\tabcellsep \multicolumn{3}{l}{363397 243255 298239}\\ Required\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Saved bits\tabcellsep \multicolumn{4}{l}{1850721 1733755 1853897 1798913}\\ RMS Error\tabcellsep 3.48\tabcellsep 5.39\tabcellsep 3.8\tabcellsep 4.7\\ \tabcellsep 8.51\tabcellsep 5.771\tabcellsep 8.62\tabcellsep 7.03\\ PSNR\tabcellsep 43.35\tabcellsep 39.55\tabcellsep 42.58\tabcellsep 40.74\\ MSE\tabcellsep 12.11\tabcellsep 29.09\tabcellsep 14.46\tabcellsep 22.11\end{longtable} \par \caption{\label{tab_20}Table 20 :}\end{figure} \footnote{© 2017 Global Journals Inc. (US)} \backmatter \begin{bibitemlist}{1} \bibitem[Ch et al. (2012)]{b7}\label{b7} \textit{}, Ch , N B Ramesh , J V Venkateswarlu , Murthy . \textit{Filter Augmented JPEG Compressions" IJCA} Dec-2012. 60 (17) p. . \bibitem[Sreelekha and Sathidevi (2007)]{b4}\label{b4} ‘+ "An Improved JPEG Compression Scheme Using Human Visual System Model’. G Sreelekha , P S Sathidevi . \textit{IEEE} June 2007. p. . \bibitem[Krishna et al. ()]{b9}\label{b9} ‘A Smoothening based JPEG Compression for an Objective Image Quality Enhancement of Regular and Noisy Images, IJAER’. Marlapalli Krishna , Prasad Reddy , Pvgd , G Srinivas . \textit{P P} 2016. 11 (6) p. . \bibitem[Srinivas et al.]{b5}\label{b5} \textit{An N-Square Approach for Reduced Complexity Non-Binary Encoding}, G Srinivas , Prasad Reddy , PV G , K Gjcst , No . XI Issue XI. p. . \bibitem[Centric JPEG Compression for an Objective Image Quality Enhancement of Noisy Images Springer, International conference on smart computing and its application PP No143 ()]{b6}\label{b6} ‘Centric JPEG Compression for an Objective Image Quality Enhancement of Noisy Images’. \textit{Springer, International conference on smart computing and its application PP No143}, 2017. p. 152. \bibitem[Xiangzhi and Fugen (2006)]{b3}\label{b3} ‘Edge Detection Based on Mathematical Morphology and Iterative Thresholding’. Bai Xiangzhi , Zhou Fugen . \textit{IEEE International Conference on Image Processing}, Nov-2006. 2 p. . \bibitem[Prakash et al. (2001)]{b2}\label{b2} ‘Enhanced JPEG Compression of Documents’. Ravi Prakash , Joan L Member , Mitchell , David A Fellow , Stepneski . \textit{IEEE International Conference on Image Processing}, Oct-2001. 3 p. . \bibitem[Marlapalli Krishna et al. (2016)]{b8}\label{b8} ‘Image Smoothening and Morphological operators Based JPEG Compression’. G Marlapalli Krishna , Prasad Srinivas , Pvgd Reddy . \textit{JATIT} March 2016. 85 (3) p. . \bibitem[De Queiroz and Member (1998)]{b1}\label{b1} ‘Processing JPEG-Compressed Images and Documents’. Ricardo L De Queiroz , Ieee Member . \textit{IEEE Transactions on Image Processing} December 1998. 7 (12) p. . \bibitem[Srinivas et al.]{b10}\label{b10} G Srinivas , P Srinivasu , T Rao , Ch Ramesh . \textit{Harmonic and Contra Harmonic Mean}, \bibitem[Egger and Li (1994)]{b0}\label{b0} ‘Very Low Bit Rate Image Coding using morphological operators and Adaptive Decompositions’. Olivier Egger , Wei Li . \textit{IEEE International Conference on Image Processing}, Nov-1994. 3 p. . \end{bibitemlist} \end{document}