•  
  •  
 

Abstract

Contrast enhancement plays a crucial role in the field of image processing. Histogram equalization is a simple and automatic method for contrast enhancement. Conventional contrast-enhancement techniques, such as histogram specification and contrast stretching, require manual parameters to achieve satisfactory results. To automatically produce enhanced results for low-contrast images, a new histogram-based optimized contrast-enhancement technique, called gray-level grouping (GLG), was proposed. GLG performs satisfactorily in dark and low-contrast images and always increases the contrast values to a maximum. Extravagant contrast enhancement typically means sacrificing the visual effects of an image. Through scrutinizing the GLG procedure, we discovered potential limitations and observed that an extra constraint on GLG enabled effective production of satisfying appearances while preserving contrast at a maximum. Experimental results showed that a simple idea led to a considerable difference in visual effects.

COinS