An HSV Model-Based Approach for the Sharpening of Color Images

An efficient approach for the sharpening of color images is proposed in this paper. For this, the image to be sharpened is first transformed to the Hue, Saturation, and Value (HSV) color model, and then only the channel of Value will be used for the process of sharpening while the other two channels are left unchanged. We then apply a proposed edge detector and low-pass filter to the channel of Value to pick out pixels around boundaries. After that, those pixels detected as around edges or boundaries are adjusted so that the boundary can be sharpened, and those non-edge pixels are kept unaltered. It is noted that the increment or decrement magnitude that is to be added to those edge pixels is determined in an adaptive manner based on global statistics of the image and local statistics of the pixel to be sharpened. With the proposed adaptive approach, the discontinuities can be highlighted while most of the original information contained in the image can be retained. Finally, the adjusted channel of Value and that of Hue and Saturation will be integrated to get the sharpened color image. In the proposed approach, a scaling factor can also be used for the adjustment of the additive magnitude so as to control the degree of discontinuity. Extensive experiments on natural images will be given in this paper to highlight the effectiveness and efficiency of the proposed approach.