A second proposed solution is a new rate adaptive control algorithm Ceritinib 1032900-25-6 for JPEG2000 [8]. The main characteristic of this new control algorithm is its mathematical model of the wavelet coefficients due to the distributive properties of the coefficients in each frequency band after the image wavelet distribution. This model can find the real contribution code rate of every encoded block prior to encoding. When the algorithm computes the plane entropy and every code block reaches the precomputed value, encoding ceases. Therefore, these two algorithms significantly improve the coding efficiency of JPEG2000. However, the experimental results show that the algorithms may lead to a decreased peak signal-to-noise ratio (PSNR) in the recovered image.

In a previous study of image recovery, a rate-distortion (R-D) estimation for fast JPEG2000 compression at low bit rates was developed [9]. However, this estimation utilizes the contexts of the wavelet coefficients, which are typically calculated during Tier-1 encoding; this context generation is a major contributor to the computational complexity of JPEG2000 compression.In this paper, an improved rate control algorithm based on the bit planes, the R-D slope, and the compression ratio is proposed. An adaptive threshold formula for Tier-1 encoding is developed. The code that passes below this threshold during Tier-1 encoding is filtered out, thereby avoiding the encoding of all of the code passes. This routine improves the coding efficiency.2. Proposed Rate Control MethodThe JPEG2000 standard algorithm consists of the wavelet transform, quantization, and EBCOT coding routines [10, 11].

EBCOT consists of two phases: Tier-1 encoding and Tier-2 encoding. The rate control in the JPEG2000 and PCRD algorithms is performed following the quantization process during Tier-1 and Tier-2 encoding, respectively. Tier-1 encoding is applied once to roughly control the bit rate [12]. GSK-3 Accurate rate control is achieved by the PCRD rate control algorithm during Tier-2 encoding, which selects the coding passes of each code block that are included in the final code stream.With Tier-1 encoding, most of the computational steps are redundant and waste memory resources. To make better use of the available resources, the characteristics of remote sensing image compression should be examined. On the one hand, as the image compression ratio becomes larger, the target bit rate of the image becomes smaller. When the accumulated bit rate is greater than the target bit rate, the bit plane number is relatively higher, as the bit plane number decreases monotonically.