Subjective Assessment of Objective Image Quality Metrics Range Guaranteeing Visually Lossless Compression

Author:

Afnan Afnan1ORCID,Ullah Faiz1ORCID,Yaseen Yaseen1ORCID,Lee Jinhee1,Jamil Sonain1ORCID,Kwon Oh-Jin1ORCID

Affiliation:

1. Department of Electronics Engineering, Sejong University, Seoul 05006, Republic of Korea

Abstract

The usage of media such as images and videos has been extensively increased in recent years. It has become impractical to store images and videos acquired by camera sensors in their raw form due to their huge storage size. Generally, image data is compressed with a compression algorithm and then stored or transmitted to another platform. Thus, image compression helps to reduce the storage size and transmission cost of the images and videos. However, image compression might cause visual artifacts, depending on the compression level. In this regard, performance evaluation of the compression algorithms is an essential task needed to reconstruct images with visually or near-visually lossless quality in case of lossy compression. The performance of the compression algorithms is assessed by both subjective and objective image quality assessment (IQA) methodologies. In this paper, subjective and objective IQA methods are integrated to evaluate the range of the image quality metrics (IQMs) values that guarantee the visually or near-visually lossless compression performed by the JPEG 1 standard (ISO/IEC 10918). A novel “Flicker Test Software” is developed for conducting the proposed subjective and objective evaluation study. In the flicker test, the selected test images are subjectively analyzed by subjects at different compression levels. The IQMs are calculated at the previous compression level, when the images were visually lossless for each subject. The results analysis shows that the objective IQMs with more closely packed values having the least standard deviation that guaranteed the visually lossless compression of the images with JPEG 1 are the feature similarity index measure (FSIM), the multiscale structural similarity index measure (MS-SSIM), and the information content weighted SSIM (IW-SSIM), with average values of 0.9997, 0.9970, and 0.9970 respectively.

Funder

the Institute for Information and Communications Technology Promotion (IITP) funded by the Korean Government

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference84 articles.

1. Smartphones, social media use and youth mental health;Naylor;Can. Med. Assoc. J.,2020

2. Aljuaid, H., and Parah, S.A. (2021). Secure patient data transfer using information embedding and hyperchaos. Sensors, 21.

3. Image compression techniques in wireless sensor networks: A survey and comparison;Lungisani;IEEE Access,2022

4. Varga, D. (2022). No-reference video quality assessment using multi-pooled, saliency weighted deep features and decision fusion. Sensors., 22.

5. Wakin, M., Romberg, J., Choi, H., and Baraniuk, R. (2002, January 22–25). Rate-distortion optimized image compression using wedge lets. Proceedings of the International Conference on Image Processing, Rochester, NY, USA.

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