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Updated: Jun 10, 2026

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
Published on: November 17, 2016
Quality assessment of deblocked images
Changhoon Yim1, Alan Conrad Bovik
1Department of Internet and Multimedia Engineering, Konkuk University, Seoul 143-701, Korea. cyim@konkuk.ac.kr
Abstract:
We study the efficiency of deblocking algorithms for improving visual signals degraded by blocking artifacts from compression. Rather than using only the perceptually questionable PSNR, we instead propose a block-sensitive index, named PSNR-B, that produces objective judgments that accord with observations. The PSNR-B modifies PSNR by including a blocking effect factor. We also use the perceptually significant SSIM index, which produces results largely in agreement with PSNR-B. Simulation results show that the PSNR-B results in better performance for quality assessment of deblocked images than PSNR and a well-known blockiness-specific index.
