ICEBIN: Image Contrast Enhancement Based on Induced Norm and Local Patch Approaches

Abstract

Traditional histogram equalization may cause degraded results of over-enhanced images under uneven illuminations. In this paper, a simple and effective image contrast enhancement method is proposed to achieve high dynamic range imaging. First, the illumination of each pixel is estimated by using an induced norm of a patch of the image. Second, a pre-gamma correction is proposed to enhance the contrast of the illumination component appropriately. The parameters of gamma correction are set dynamically based on the local patch of the image. Third, an automatic Contrast-Limited Adaptive Histogram Equalization (CLAHE) whose clip point is automatically set is applied to the processed image for further image contrast enhancement. Fourth, a noise reduction algorithm based on the local patch is developed to reduce image noise and increase image quality. Finally, a post-gamma correction is applied to slightly enhance the dark regions of images and not affect the brighter areas. Experimental results show that the proposed method has its superiority over several state-of-the-art enhancement quality techniques by using qualitative and quantitative evaluations.

Keywords

• Contrast enhancement
• contrast-limited adaptive histogram equalization
• gamma correction
• high dynamic range
• induced norm
• noise reduction