Gradient-guided color image contrast and saturation enhancement

Abstract

Digital color images are capable of presenting hue, saturation, and brightness perceptions. Therefore, quality improvement of color images should be taken into account to enhance all three stimuli. An effective method is proposed that aims at enriching the colorfulness, vividness, and contrast of color images simultaneously. In this method, color correction based on magnitude stretching is carried out first, image enhancement is then derived from an intensity-guided operation that concurrently improves the contrast and saturation qualities. Furthermore, the proposed methodology mitigates the heavy computational burden arising from the need to transform the source color space into an alternative color space in conventional approaches. Experiments had been conducted using a collection of real-world images captured under various environmental conditions. Image quality improvements were observed both from subjective viewing and quantitative evaluation metrics in colorfulness, saturation, and contrast.

Blackberry Fruit Classification in Underexposed Images Combining Deep Learning and Image Fusion Methods

“…Here, we add the definition of each evaluation metric to improve the reproducibility of the results and avoid ambiguities because, for example, C can be defined in different ways according to the context or the author. C measures the difference between regions in the image, translated into better discrimination between the background and regions of interest (ROIs) by Equation (1), where I(i, j) is the intensity of the pixel image, and n and m are the width and height of the image, respectively [31]…”

“…Finally, S in an image measures the intensity or depth of color; a very brightly colored image has a high saturation value. On the contrary, low values of S mean that the image appears to be shaded, without brightness [31]. However, the value must be maintained as close as possible to the original image value to avoid color over-saturation or undersaturation.…”