Just-Noticeable Difference-Based Perceptual Optimization for JPEG Compression

• Main Authors: Zhang, Xinfeng, Wang, Shiqi, Gu, Ke, Lin, Weisi, Ma, Siwei, Gao, Wen
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2017
• Subjects: Just-noticeable difference (JND); Image compression
• Online Access: https://hdl.handle.net/10356/83520; http://hdl.handle.net/10220/42621
• Institution: Nanyang Technological University

The Quantization table in JPEG, which specifies the quantization scale for each discrete cosine transform (DCT) coefficient, plays an important role in image codec optimization. However, the generic quantization table design that is based on the characteristics of human visual system (HVS) cannot adapt to the variations of image content. In this letter, we propose a just-noticeable difference (JND) based quantization table derivation method for JPEG by optimizing the rate-distortion costs for all the frequency bands. To achieve better perceptual quality, the DCT domain JND-based distortion metric is utilized to model the stair distortion perceived by HVS. The rate-distortion cost for each band is derived by estimating the rate with the first-order entropy of quantized coefficients. Subsequently, the optimal quantization table is obtained by minimizing the total rate-distortion costs of all the bands. Extensive experimental results show that the quantization table generated by the proposed method achieves significant bit-rate savings compared with JPEG recommended quantization table and specifically developed quantization tables in terms of both objective and subjective evaluations.