Contrast enhancement algorithm for colour images

Conventional contrast enhancement techniques often fail to produce satisfactory results for low-contrast images, and cannot be automatically applied to different images because processing parameters must be specified manually to produce satisfactory results for a given image. This paper proposes a contrast enhancement technique to enhance colour images captured under poor illumination and varying environmental conditions. Images are converted from RGB to HSV colour space where enhancement is achieved and reconverted to the RGB. Class Limited Adaptive Histogram Equalization (CLAHE) is used to enhance the luminance component (V). Discrete Wavelet Transform is applied to the Saturation (S) components, and the decomposed approximation coefficients are modified by a mapping function derived from scaling triangle transform. The enhanced S component is obtained through Inverse Wavelet transforms. The image is then converted back to the RGB colour space. Subjective (visual quality inspection) and objective parameters (Peak-signal-to-noise ratio (PSNR), Absolute Mean Brightness Error (AMBE) and Mean squared error (MSE)) were used for performance evaluation. The algorithm implemented in MATLAB was tested images and compared with outputs of HE and CLAHE enhancement techniques. The result shows that the new algorithm gave the best performance of the three methods.