Texture segmentation using hierarchical wavelet decomposition

E Salari, Z Ling - Pattern Recognition, 1995 - Elsevier
E Salari, Z Ling
Pattern Recognition, 1995Elsevier
This paper presents a texture segmentation algorithm based on a hierarchical wavelet
decomposition. Using Daubechies four-tap filter, an original image is decomposed into three
detail images and one approximate image. The decomposition can be recursively applied to
the approximate image to generate a lower resolution of the pyramid. The segmentation
starts at the lowest resolution using the K-means clustering scheme and textural features
obtained from various sub-bands. The result of segmentation is propagated through the …
This paper presents a texture segmentation algorithm based on a hierarchical wavelet decomposition. Using Daubechies four-tap filter, an original image is decomposed into three detail images and one approximate image. The decomposition can be recursively applied to the approximate image to generate a lower resolution of the pyramid. The segmentation starts at the lowest resolution using the K-means clustering scheme and textural features obtained from various sub-bands. The result of segmentation is propagated through the pyramid to a higher resolution with continuously improving the segmentation. The lower resolution levels help to build the contour of the segmented texture, while higher levels refine the process, and correct possible errors.
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