基于灰度值分割的感兴趣区域图像压缩算法

摘要

A new region of interest (ROI) image compression algorithm is proposed based on the ROI image compression standards in JPEG2000. According to the ROI compression condition assigned by users, the most significant bitplanes of gray-scale is determined, and the grayscale is partitioned into the most significant grayscale and the secondary gray value. The most significant one is coded firstly, and then the secondary gray values are further coded according to the bit rate requirements. The experimental results whow that the proposed algorithm has the advantages of the maximum translation method and the general translation method, can not only control the image compression quality in ROI and background flexibly, but also support the ar-bitrarily shaped ROI coding without coding shape information. Additionally, the method can improve the computing speed and save the memory space at low bit rate due to the grayscale partition before the wavelet transform.%基于JPEG2000中感兴趣区域(ROI)图像压缩标准,提出了一种新型ROI图像压缩算法.算法根据用户指定的ROI条件,确定灰度值的重要位平面,然后将灰度值分割为重要灰度值和次要灰度值,优先对重要灰度值进行编码.根据比特率要求对次要灰度值进一步编码.实验结果表明:提出的算法同时具有最大平移法和一般平移法的优点,不仅能够灵活控制ROI和背景区域图像质量在码率上的分配,还能支持任意形状的ROI编码而不需要编码形状信息.另外,由于在小波变换前就进行了灰度值分割,所以在低码率时能够有效提高计算速度并节省存储空间.