Analyzing the Effect of JPEG Compression on Local Variance of Image Intensity

Jianquan Yang, Guopu Zhu, Yun Qing Shi

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

The local variance of image intensity is a typical measure of image smoothness. It has been extensively used, for example, to measure the visual saliency or to adjust the filtering strength in image processing and analysis. However, to the best of our knowledge, no analytical work has been reported about the effect of JPEG compression on image local variance. In this paper, a theoretical analysis on the variation of local variance caused by JPEG compression is presented. First, the expectation of intensity variance of 8×8 non-overlapping blocks in a JPEG image is derived. The expectation is determined by the Laplacian parameters of the discrete cosine transform coefficient distributions of the original image and the quantization step sizes used in the JPEG compression. Second, some interesting properties that describe the behavior of the local variance under different degrees of JPEG compression are discussed. Finally, both the simulation and the experiments are performed to verify our derivation and discussion. The theoretical analysis presented in this paper provides some new insights into the behavior of local variance under JPEG compression. Moreover, it has the potential to be used in some areas of image processing and analysis, such as image enhancement, image quality assessment, and image filtering.

Original languageEnglish (US)
Article number7452379
Pages (from-to)2647-2656
Number of pages10
JournalIEEE Transactions on Image Processing
Volume25
Issue number6
DOIs
StatePublished - Jun 2016

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design

Keywords

  • JPEG compression
  • Laplacian distribution
  • Local variance
  • discrete cosine transform (DCT)

Fingerprint Dive into the research topics of 'Analyzing the Effect of JPEG Compression on Local Variance of Image Intensity'. Together they form a unique fingerprint.

Cite this