Contrast enhancement of night images

• Published in: 2016 International Conference on Machine Learning and Cybernetics (ICMLC) Vol. 1; pp. 380 - 385
• Main Authors: Priyanka, Steffi Agino, Hsiao-Jung Tung, Yuan Kai Wang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2016
• Subjects: Brightness; Colored noise; Contrast enhancement; Cybernetics; Denoising; Histogram smoothing; Histograms; Image edge detection; Noise reduction; Principal component analysis; Simulation
• ISSN: 2160-1348
• DOI: 10.1109/ICMLC.2016.7860931

Night images obtained from a surveillance camera have low visibility compared to daytime images. Images captured at night have low brightness, low contrast and high noise. A modified contrast enhancement (CE) algorithm was proposed and developed in luminance-chrominance space. Only the luminance channel obtained by PCA transform is processed as it contains the most valuable information. Daytime images are simulated with various degrees of contrast and Poisson noise using MATLAB. CE algorithm is applied in three scales to obtain good brightness and contrast of the images. Images are denoised by using bilateral filter that smoothes the noise while preserving edges. The brightness and contrast of the night images have been enhanced significantly and the noise is reduced effectively, preserving the details of the images. Finally, the performance of the proposed algorithm is illustrated by processing images under various lighting conditions without introducing halo and ghosting artifacts. Structural similarity and visual contrast measures demonstrate that the proposed method is more effective over other existing methods.