Camouflage aims at making objects disappearing in the background environment by presenting similar textures, color information and patterns with the background. The camouflage objects can be divided into two groups: dark camouflage and light camouflage. To locate the camouflage objects, many existing detection algorithms have been published. And, their performance is highly related to the image enhancement as their pre-processes. Even though existing histogram equalization-based image enhancement algorithms perform well at either dark camouflage image or light camouflage image, there is still a challenge to deal with an image containing both dark camouflage and light camouflage. To meet this challenge, a new hill climbing-based histogram equalization algorithm is proposed to follow a three-step framework of segmentation, enhancement and integration. Different from existing approaches, this proposed method aims at segmenting the dark camouflage content and light camouflage content by utilizing the hill climbing algorithm. The segmented camouflage contents are enhanced by their corresponding histogram equalization. Finally, the enhanced segments are combined by an integration process to get the final output images with a satisfied quality. This hill climbingbased histogram equalization can enhance the detailed structural information in both dark and light regions of images simultaneously. Experimental and comparison results demonstrate its superior performance.
Color transfer changes the color contents of a target image by replacing the colors in the target image with colors from another source image. The target image will be repainted/recolored to exhibit the same ambience as the source image. Color transfer is applicable to a wide range of commercial image processing tools and products. While much outstanding research has been conducted on this subject, judging the performance of the recoloring process remains subjective to human evaluation. To obtain an objective quantitative assessment of recoloring algorithms’ performance, a new color transfer quality measure is proposed. In this paper, we will first establish the requirements that a good color transfer quality measure should meet. Then, according to these requirements, a new color transfer quality measure is proposed that focuses on measuring the content similarity between a target image and a resulting recolored output image, and the color similarity between the source image and the output image. To demonstrate the performance of the proposed measure, the subjective human perception Mean Opinion Score (MOS) values are used. The high correlation between MOS and the proposed measure demonstrate the measure’s performance and demonstrate that it exhibits high consistency with human perception.
Most existing image encryption algorithms often transfer the original image into a noise-like image which is an apparent visual sign indicating the presence of an encrypted image. Motivated by the data hiding technologies, this paper proposes a novel concept of image encryption, namely transforming an encrypted original image into another meaningful image which is the final resulting encrypted image and visually the same as the cover image, overcoming the mentioned problem. Using this concept, we introduce a new image encryption algorithm based on the wavelet decomposition. Simulations and security analysis are given to show the excellent performance of the proposed concept and algorithm.
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