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- W3110631775 abstract "Fractal dimension (FD) effectively quantifies the roughness of the image surface, which can be applied to many image processing applications. Although a number of methods are available to calculate FD of grayscale images, limited work is done for the color images. In this paper, a new method is proposed to estimate FD of color images in CIE L*a*b* (CIELAB) color space. Firstly, the color image is converted to CIELAB space. Secondly, each of the L, a, and b components of CIELAB space are divided into overlapped grids and $$n_{r}$$ value of each corresponding grid at different sizes are obtained using the distance between the minimum and maximum (L, a, b) triplets, where $$n_{r}$$ is the number of boxes that constitute the intensity variations over a grid with scale, r. Thirdly, $$n_{r}$$ values of the same sized grids are accumulated to obtain the $$N_{r}$$ values. Finally, robust least squares regression (RLS) is applied to these $$N_{r}$$ values to obtain the FD value. Three latest methods are adopted to differentiate the performance of the proposed method using the synthesized fractal Brownian motion (FBM) and Brodatz image databases. Experimental results show that the proposed method is more accurate in estimating the FD of color images." @default.
- W3110631775 created "2020-12-07" @default.
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- W3110631775 date "2020-11-24" @default.
- W3110631775 modified "2023-09-26" @default.
- W3110631775 title "A New Technique for Estimating Fractal Dimension of Color Images" @default.
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- W3110631775 doi "https://doi.org/10.1007/978-981-15-7834-2_24" @default.
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