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BlinQS: Blind quality scalable image compression algorithm without using PCRD optimization
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DOI：10.1007/s11042-023-15454-2.png)
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Abstract
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Quality Scalability is one of the important features of interactive imaging to obtain better perceptual quality at a specified target bit rate. In JPEG 2000, it is achieved using quality layers obtained by Rate-Distortion (R-D) optimization techniques in Tier-II coding. Some important concerns here are: (i) inefficient conventional Post-Compression Rate-Distortion (PCRD) optimization algorithms, (ii) lack of quality scalability for less or single quality layer string. This paper takes the above mentioned concerns into account and proposes a Blind Quality Scalable (BlinQS) algorithm that provides scalability with the least computational complexity. The novel part of this method is to eliminate the Tier-II coding and add a blind string selection i.e., transcoding algorithm through a normal distribution function for efficient rate control. The results obtained suggest that the proposed method achieves better results than JPEG-2000 at single quality layer and achieves results close to JPEG-2000 without using PCRD optimization algorithms.
Keywords:
Blind quality scalability (BlinQS)
Image compression
Rate-distortion optimization
JPEG-2000 standard
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