Improved JPEG Coding by Filtering 8 × 8 DCT Blocks

Author:

Iqbal YasirORCID,Kwon Oh-JinORCID

Abstract

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.

Funder

Institute of Information & communications Technology Planning & Evaluation

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Analysis of Adaptive, Entropy and Wavelet based Coding Techniques- A Survey;2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC);2022-11-10

2. New and Specialized Methods of Image Compression;Journal of Imaging;2022-02-16

3. Orchestrating Image Retrieval and Storage over A Cloud System;IEEE Transactions on Cloud Computing;2022

4. Impact of Image Compression on the Performance of Steel Surface Defect Classification with a CNN;Journal of Sensor and Actuator Networks;2021-12-16

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