Image block matching based on GLCM (gray level co-occurence matrix) texture feature on grayscale image auto coloring

Muhammad Sipan, N. S. M. Susiki, E. M. Yuniarno
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引用次数: 3

Abstract

Colorization is a coloring process in the image or video, which is done to provide detail and clarity to the image or video. This study used image gray scale to be colored by matching both color image pixel blocks and grayscale images based on GLCM texture feature (gray level co-occurance matrix) using a sum of absolute difference. Color image blocks are used as templates and grayscale image blocks as targets, searching for similarities between two image blocks by subtracting both GLCM texture feature values and comparing the target of GLCM value with the template value to obtain the smallest or near-zero value in the color block. The smallest in the color image block is a pair of grayscale image blocks, as both have similar features of the GLCM texture. Further, color of color image blocks are transferred to the grayscale block in accordance with the existing resemblance (pair), until all areas that have similarity are colored.
基于灰度共生矩阵纹理特征的灰度图像块匹配
着色是在图像或视频中着色的过程,它是为了使图像或视频提供细节和清晰度。本研究基于GLCM纹理特征(灰度共生矩阵),采用绝对差和对彩色图像像素块与灰度图像进行匹配,对图像灰度进行着色。以彩色图像块为模板,灰度图像块为目标,通过减去两个图像块的GLCM纹理特征值,并将GLCM值的目标与模板值进行比较,寻找两个图像块之间的相似性,从而获得色块中最小或接近于零的值。彩色图像块中最小的是一对灰度图像块,因为两者具有相似的GLCM纹理特征。进一步,将彩色图像块的颜色按照已有的相似性(对)转移到灰度块中,直到所有具有相似性的区域都上色。
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