Contrast Enhancement of Image Using Dynamic Range between Histogram Valley and Gamma Transformation

Contrast enhancement is a pre-processing stage in image processing, which plays a further significant role in various applications. This research paper proposes a hybrid approach of contrast enhancement by combining two techniques, brightness preserving dynamic histogram equalization and gamma transformation based on skewness of histogram. The brightness preserving dynamic equalization method is used to preserve the peak of histogram by mapping the valley between two peaks. Thereafter, gamma correction based on skewness is employed to adjust the histogram from under-enhancement and over-enhancement of resultant image. This technique is simulated on various dataset and real time image, and compared with other existing techniques. The simulation are evaluated by visual assessment and quantitative metrics. Average peak signal to noise ratio, entropy and absolute mean brightness error values are 25.86, 6.09 and 38.68 of standard dataset image and 29.01, 6.62 and 24.44 respectively for real time images which depicts improved image quality and better visualization of details as compared to some existing methods.