Lossless Contrast Enhancement of Color Images with Reversible Data Hiding

Abstract

Recently, lossless contrast enhancement (CE) has been proposed so that a contrast-changed image can be converted to its original version by maintaining information entropy in it. As most of the lossless CE methods are proposed for grayscale images, artifacts are probably introduced after directly applying them to color images. For instance, color distortions may be caused after CE is separately conducted in each channel of the RGB (red, green, and blue) model. To cope with this issue, a new scheme is proposed based on the HSV (hue, saturation, and value) color model. Specifically, both hue and saturation components are kept unchanged while only the value component is modified. More precisely, the ratios between the RGB components are maintained while a reversible data hiding method is applied to the value component to achieve CE effects. The experimental results clearly show CE effects obtained with the proposed scheme, while the original color images can be perfectly recovered. Several metrics including image entropy were adopted to measure the changes made in CE procedure, while the performances were compared with those of one existing scheme. The evaluation results demonstrate that better image quality and increased information entropy can be simultaneously achieved with our proposed scheme.

An Extension of Reversible Image Enhancement Processing for Saturation and Brightness Contrast

“…Therefore, it is desired to restore the original images from the output images without increasing the data amount. Reversible contrast enhancement (CE) [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] using reversible data hiding (RDH) is a technique where the brightness contrast can be flexibly enhanced and reverted without increases in data.…”

“…If we simply use those methods for color images, some image distortion can appear in the output images. In contrast, some CE methods [13,14] have been proposed for color images. The images restored with these methods have a high image quality, but they do not perfectly match their originals.…”

Contrast Enhancement of Digital Images Using an Improved Type-II Fuzzy Set-Based Algorithm

“…Degradations are deemed as unwanted effects that reduce the visible quality of digital images making them unlikely to be used for different applications. One of the most common degradations that affect digital images is the low-contrast effect [5], which can occur due to lack of user experience, faulty camera settings, hardware or software limitations, nature of the environment, and deficient lighting conditions [6]. The contrast is usually described as the variance between the darkest and the brightest values of the image [7].…”

Generalized Reversible Data Hiding with Content-Adaptive Operation and Fast Histogram Shifting Optimization

“…Reversible data hiding (RDH) [ 1 , 2 ], also called reversible watermarking (RW), is referred to as the art of embedding extra data, such as source information and authentication data, into a host signal (also called cover) by slightly modifying the host signal. The embedded information and the original host signal can be fully reconstructed from the marked content by a legal receiver [ 3 , 4 ]. As RDH enables us to perfectly recover the original host content, it is quite desirable and helpful in some sensitive scenarios, such as medical image processing, remote sensing, and military communication.…”