An image retrieval method based on spatial distribution of color

Color histogram is now widely used in image retrieval. Color histogram-based image retrieval methods are simple and efficient but without considering the spatial distribution information of the color. To overcome the shortcoming of conventional color histogram-based image retrieval methods, an image retrieval method based on Radon Transform （RT） is proposed. In order to reduce the computational complexity, wavelet decomposition is used to compress image data. Firstly, images are decomposed by Mallat algorithm. The low-frequency components are then projected by RT to generate the spatial color feature. Finally the moment feature matrices which are saved along with original images are obtained. Experimental results show that the RT based retrieval is more accurate and efficient than traditional color histogram-based method in case that there are obvious objects in images. Further more, RT based retrieval runs significantly faster than the traditional color histogram methods.     

BIQI和JND相结合的图像增强客观评价方法

提出一种结合盲图像质量指标(BIQI )和临界可见偏差(JND)的图像增强 客观评价方法。方法基于Retinex理论,将测试图像分成反射图像和照度图像 ,分别对反射图像和照度图 像进行BIQI和JND评分,得到的评分之和作为图像增强客观评价得分。对原图 像失真和背景亮 度的变量控制系列的实验表明,Retinex分解得到的反射图像只受失真的种类 和失真程度影响,而照度图像代表 原图像环境光照信息具有亮度阈值效应;应用本文算法对增强后的图像评分得到Score的 最高分为 0.609,与主观评价结果一致;而PSNR、SSIM的评分都是和原图像本身比较, 不能表明图像增强效果。实验结果表明,本文算法的评价结果与主观视觉一致,能用于定量 对图像增强进行客观评价。