Contrast-based image enhancement algorithm using grey-scale and colour space

The method presented encodes red, green and blue (RGB) images. When RGB images are added, the result inherently becomes darker due to summation of grey-scale images. This image is enhanced by adjusting brightness and contrast to achieve a visually pleasing image. The method developed uses hue saturation value (HSV) and contrast enhancement (CE) to obtain enhanced color images. It can be used to combine imaging modality of a multimodal data set to represent multimodal data sets in color image without data loss. In HSV color space, grey scale and color information are in separate channels, so the combined images do not suffer from the same darkening contrast as the images combined in RGB color space suffer. The method proposed first involves computation of mapping function, then gradient-based function is calculated to map image gradients based on grey-level (GL) intensity and eigenvalue computation is used for CE. Therefore, the contrast of GL components of gradient of an image is enhanced by a mapping function. A better visual output is ensured using the proposed algorithm which is evaluated using performance metrics. When compared to adaptive histogram equalisation and contrast-based imaging algorithms, the proposed technique gives significant performance in contrast and color enhancement.