Directional Texture Feature Extraction using Context Labels of Significance Coding for JPEG2000 Compressed Domain Image Retrieval

Wavelet transforms is a widely used technique for analysing and describing texture patterns of image. Another advantage of wavelet transform is that one can analyse textures with multiresolution and can classify directional texture pattern information into each directional subband. Where as, HL subband implies horizontal frequency information, LH subband implies vertical frequency information and HH subband implies diagonal frequency. Nevertheless, many wavelet-based image retrieval approaches are not good tool to use directional subband information, obtained by wavelet transforms, for efficiently directional texture pattern classification of retrieved images. This paper proposes a novel image retrieval technique in JPEG2000 compressed domain using image significant map to compute an image context in order to construct image index. Experimental results indicate that the proposed method can effectively differentiate and categorize images with different texture directional information as compared to other known methods.