Comparative Assessment of Color Models for Multi-Focus Image Fusion With Optimal Cluster Size - Dharmaraj, J.R; Durairaj, D.C; Melodina, J.J (International Journal of Computer Sciences and Engineering, 2018)
This paper assesses comparatively the performance of image fusion in different color channels using an image matting based multi focus image fusion technique, the JR method. This is a solely vicinity-based image matting algorithm that relies on the close pixel clusters in the input images. Color spaces provide powerful information for image processing by means of color variants, color histogram, color texture etc.. In our assessment, firstly we transform RGB color model of multi focus source images in to 6 different color spaces that are HSV, L*a*b, YUV, YIQ, YCbCr and XYZ. Next, each color channel of input images (RGB-R, RGB-G, RGB-B, LAB-L, LAB-A, LAB-B, HSV-H, HSV-S, HSV-V, YUV-Y,YUV-U, YUV-V, XYZX, XYZ-Y,XYZ-Z, YCbCr-Y, YCbCr-Cb, YCbCr –Cr, YIQ-Y, YIQ-I, YIQ-Q) are used in fusion process using the image matting based multi focus image fusion with optimal cluster size (the JR method). Finally the fused images are assessed with standard image quality metrics. The results certainly show better results in LAB-L and YIQ-Q color channals.