Title :
Local radius index - a new texture similarity feature
Author :
Yuanhao Zhai ; Neuhoff, David L. ; Pappas, Thrasyvoulos N.
Author_Institution :
EECS Dept., Univ. of Michigan, Ann Arbor, MI, USA
Abstract :
We develop a new type of statistical texture image feature, called a Local Radius Index (LRI), which can be used to quantify texture similarity based on human perception. Image similarity metrics based on LRI can be applied to image compression, identical texture retrieval and other related applications. LRI extracts texture features by using simple pixel value comparisons in space domain. Better performance can be achieved when LRI is combined with complementary texture features, e.g., Local Binary Patterns (LBP) and the proposed Subband Contrast Distribution. Compared with Structural Texture Similarity Metrics (STSIM), the LRI-based metrics achieve better retrieval performance with much less computation. Applied to the recently developed structurally lossless image coder, Matched Texture Coding, LRI enables similar performance while significantly accelerating the encoding.
Keywords :
data compression; feature extraction; image coding; image texture; statistical analysis; LBP; LRI; STSIM; human perception; identical texture retrieval; image compression; local binary patterns; local radius index; lossless image coder; matched texture coding; pixel value comparisons; statistical texture image feature; structural texture similarity metrics; subband contrast distribution; texture feature extraction; texture similarity feature; Histograms; IP networks; Image coding; Image edge detection; Indexes; Measurement; Vectors; image coding; retrieval; texture similarity;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
DOI :
10.1109/ICASSP.2013.6637888