Improved JPEG Coding by Filtering 8 × 8 DCT Blocks

The JPEG format, consisting of a set of image compression techniques, is one of the most commonly used image coding standards for both lossy and lossless image encoding. In this format, various techniques are used to improve image transmission and storage. In the final step of lossy image coding, JP...

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Main Authors: Yasir Iqbal, Oh-Jin Kwon
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Journal of Imaging
Subjects:
Online Access:https://www.mdpi.com/2313-433X/7/7/117
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spelling doaj-94e0d2a847d74e2ebe85a1238c9efa922021-07-23T13:48:34ZengMDPI AGJournal of Imaging2313-433X2021-07-01711711710.3390/jimaging7070117Improved JPEG Coding by Filtering 8 × 8 DCT BlocksYasir Iqbal0Oh-Jin Kwon1Department of Electrical Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, KoreaDepartment of Electrical Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, KoreaThe JPEG format, consisting of a set of image compression techniques, is one of the most commonly used image coding standards for both lossy and lossless image encoding. In this format, various techniques are used to improve image transmission and storage. In the final step of lossy image coding, JPEG uses either arithmetic or Huffman entropy coding modes to further compress data processed by lossy compression. Both modes encode all the 8 × 8 DCT blocks without filtering empty ones. An end-of-block marker is coded for empty blocks, and these empty blocks cause an unnecessary increase in file size when they are stored with the rest of the data. In this paper, we propose a modified version of the JPEG entropy coding. In the proposed version, instead of storing an end-of-block code for empty blocks with the rest of the data, we store their location in a separate buffer and then compress the buffer with an efficient lossless method to achieve a higher compression ratio. The size of the additional buffer, which keeps the information of location for the empty and non-empty blocks, was considered during the calculation of bits per pixel for the test images. In image compression, peak signal-to-noise ratio versus bits per pixel has been a major measure for evaluating the coding performance. Experimental results indicate that the proposed modified algorithm achieves lower bits per pixel while retaining quality.https://www.mdpi.com/2313-433X/7/7/117JPEG image codingimage compressionJPEG entropy coding
collection DOAJ
language English
format Article
sources DOAJ
author Yasir Iqbal
Oh-Jin Kwon
spellingShingle Yasir Iqbal
Oh-Jin Kwon
Improved JPEG Coding by Filtering 8 × 8 DCT Blocks
Journal of Imaging
JPEG image coding
image compression
JPEG entropy coding
author_facet Yasir Iqbal
Oh-Jin Kwon
author_sort Yasir Iqbal
title Improved JPEG Coding by Filtering 8 × 8 DCT Blocks
title_short Improved JPEG Coding by Filtering 8 × 8 DCT Blocks
title_full Improved JPEG Coding by Filtering 8 × 8 DCT Blocks
title_fullStr Improved JPEG Coding by Filtering 8 × 8 DCT Blocks
title_full_unstemmed Improved JPEG Coding by Filtering 8 × 8 DCT Blocks
title_sort improved jpeg coding by filtering 8 × 8 dct blocks
publisher MDPI AG
series Journal of Imaging
issn 2313-433X
publishDate 2021-07-01
description The JPEG format, consisting of a set of image compression techniques, is one of the most commonly used image coding standards for both lossy and lossless image encoding. In this format, various techniques are used to improve image transmission and storage. In the final step of lossy image coding, JPEG uses either arithmetic or Huffman entropy coding modes to further compress data processed by lossy compression. Both modes encode all the 8 × 8 DCT blocks without filtering empty ones. An end-of-block marker is coded for empty blocks, and these empty blocks cause an unnecessary increase in file size when they are stored with the rest of the data. In this paper, we propose a modified version of the JPEG entropy coding. In the proposed version, instead of storing an end-of-block code for empty blocks with the rest of the data, we store their location in a separate buffer and then compress the buffer with an efficient lossless method to achieve a higher compression ratio. The size of the additional buffer, which keeps the information of location for the empty and non-empty blocks, was considered during the calculation of bits per pixel for the test images. In image compression, peak signal-to-noise ratio versus bits per pixel has been a major measure for evaluating the coding performance. Experimental results indicate that the proposed modified algorithm achieves lower bits per pixel while retaining quality.
topic JPEG image coding
image compression
JPEG entropy coding
url https://www.mdpi.com/2313-433X/7/7/117
work_keys_str_mv AT yasiriqbal improvedjpegcodingbyfiltering88dctblocks
AT ohjinkwon improvedjpegcodingbyfiltering88dctblocks
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