Title :
Modified luminance based MSR for fast and efficient image enhancement
Author :
Tao, Li ; Asar, Vijayan
Author_Institution :
Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA
Abstract :
A luminance based multi scale retinex (LB_MSR) algorithm for the enhancement of darker images is proposed in this paper. The new technique consists only the addition of the convolution results of 3 different scales. In this way, the color noise in the shadow/dark areas can be suppressed and the convolutions with different scales can be calculated simultaneously to save CPU time. Color saturation adjustment for producing more natural colors is implemented. Each spectral band can be adjusted based on the enhancement of the intensity of the band and by using a color saturation parameter. The color saturation degree can be automatically adjusted according to different types of images by compensating the original color saturation in each band. Luminance control is applied to prevent the unwanted luminance drop at the uniform luminance areas by automatically detecting the luminance drop and keeping the luminance up to certain level that is evaluated from the original image. Down-sized convolution is used for fast processing and then the result is re-sized back to the original size. Performance of the new enhancement algorithm is tested in various images captured at different lighting conditions. It is observed that the new technique outperforms the conventional MSR technique in terms of the quality of the enhanced images and computational speed.
Keywords :
Gaussian processes; brightness; convolution; image colour analysis; image denoising; image enhancement; image restoration; Gaussian function; color noise suppression; color saturation; down sized convolution; image capture; image enhancement; luminance control; luminance drop detection; modified luminance based multi scale retinex; Automatic control; Colored noise; Convolution; Dynamic range; Gaussian processes; Histograms; Image enhancement; Laboratories; Testing; Very large scale integration;
Conference_Titel :
Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. 32nd
Print_ISBN :
0-7695-2029-4
DOI :
10.1109/AIPR.2003.1284268