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4 March 2013 MRF model with adaptive multiresolution for image segmentation
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Proceedings Volume 8761, PIAGENG 2013: Image Processing and Photonics for Agricultural Engineering; 876107 (2013) https://doi.org/10.1117/12.2019620
Event: Third International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2013), 2013, Sanya, China
Abstract
This paper proposes a Markov random field (MRF) model with adaptive selection multiresolution (MRF-AM) for texture image segmentation. By considering the wavelet decomposition and the morphological wavelet decomposition, MRFAM adaptively selects the multiresolution representation as features from the wavelet and morphological wavelet stepby- step. Then, the MRF is employed to model the features of adaptive multiresolution. The segmentation results are finally obtained by maximizing a posterior probability of the MRF. Experiments demonstrate that our method can improve the segmentation accuracy compared with the deterministic multi-resolution method.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qinling Dai, Chen Zheng, Dingqian Sun, and Leiguang Wang "MRF model with adaptive multiresolution for image segmentation", Proc. SPIE 8761, PIAGENG 2013: Image Processing and Photonics for Agricultural Engineering, 876107 (4 March 2013); https://doi.org/10.1117/12.2019620
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