Kuo C J, Lin C H, Yeh C H
Signal and Med. Labs., Nat. Chung Cheng Univ., Chiayi.
IEEE Trans Image Process. 1999;8(1):33-40. doi: 10.1109/83.736682.
Noise reduction of VQ encoded images is achieved through the proposed anti-gray coding (AGC) and noise detection and correction scheme. In AGC, binary indices are assigned to the codevector in such a way that the 1-b neighbors of a code vector are as far apart as possible. To detect the channel errors, we first classify an image into uniform and edge regions. Then we propose a mask to detect the channel errors based on the image classification (uniform or edge region) and the characteristics of AGC. We also mathematically derive a criterion for error detection based on the image classification. Once error indices are detected, the recovered indices can be easily chosen from a "candidate set" by minimizing the gray-level transition across the block boundaries in a VQ encoded image. Simulation results show that the proposed technique provides detection results with smaller than 0.1% probability of error and more than 86.3% probability of detection at a random bit error rate of 0.1%, while the undetected errors are invisible. In addition, the proposed detection and correction techniques improve the image quality (compared with that encoded by AGC) by 3.9 dB.
通过所提出的抗灰度编码（AGC）以及噪声检测与校正方案实现了矢量量化（VQ）编码图像的降噪。在AGC中，以这样一种方式为码矢量分配二进制索引：使得码矢量的1 - b邻域尽可能相距遥远。为了检测信道错误，我们首先将图像分类为均匀区域和边缘区域。然后，我们基于图像分类（均匀或边缘区域）以及AGC的特性提出一种掩码来检测信道错误。我们还基于图像分类在数学上推导了一个错误检测准则。一旦检测到错误索引，通过最小化VQ编码图像中跨块边界的灰度级转换，可以很容易地从“候选集”中选择恢复的索引。仿真结果表明，在随机误码率为0.1%时，所提出的技术提供的检测结果误码概率小于0.1%，检测概率大于86.3%，而未检测到的错误是不可见的。此外，所提出的检测和校正技术将图像质量（与AGC编码的图像相比）提高了3.9 dB。
