  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
algorithm through a normal distribution 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.
