Weak-Light Image Enhancement Method Based on Adaptive Local Gamma Transform and Color Compensation

This article proposes a correction method for image enhancement models based on an adaptive local gamma transformation and color compensation inspired by the illumination reflection model. It is demonstrated that the proposed method adaptively reduces the influence of uneven illumination to avoid overenhancement and improves the visual effect of low-light images

Contrast Enhancement of Brightness-Distorted Images by Improved Adaptive Gamma Correction

As an efficient image contrast enhancement (CE) tool, adaptive gamma correction (AGC) was previously proposed by relating gamma parameter with cumulative distribution function (CDF) of the pixel gray levels within an image. ACG deals well with most dimmed images, but fails for globally bright images and the dimmed images with local bright regions. Such two categories of brightness-distorted images are universal in real scenarios, such as improper exposure and white object regions. In order to attenuate such deficiencies, here we propose an improved AGC algorithm. The novel strategy of negative images is used to realize CE of the bright images, and the gamma correction modulated by truncated CDF is employed to enhance the dimmed ones. As such, local over-enhancement and structure distortion can be alleviated. Both qualitative and quantitative experimental results show that our proposed method yields consistently good CE results

A Retinex-based Image Enhancement Scheme with Noise Aware Shadow-up Function

This paper proposes a novel image contrast enhancement method based on both a noise aware shadow-up function and Retinex (retina and cortex) decomposition. Under low light conditions, images taken by digital cameras have low contrast in dark or bright regions. This is due to a limited dynamic range that imaging sensors have. For this reason, various contrast enhancement methods have been proposed. Our proposed method can enhance the contrast of images without not only over-enhancement but also noise amplification. In the proposed method, an image is decomposed into illumination layer and reflectance layer based on the retinex theory, and lightness information of the illumination layer is adjusted. A shadow-up function is used for preventing over-enhancement. The proposed mapping function, designed by using a noise aware histogram, allows not only to enhance contrast of dark region, but also to avoid amplifying noise, even under strong noise environments.Comment: To appear in IWAIT-IFMIA 201

Implementation of Adaptive Unsharp Masking as a pre-filtering method for watermark detection and extraction

Digital watermarking has been one of the focal points of research interests in order to provide multimedia security in the last decade. Watermark data, belonging to the user, are embedded on an original work such as text, audio, image, and video and thus, product ownership can be proved. Various robust watermarking algorithms have been developed in order to extract/detect the watermark against such attacks. Although watermarking algorithms in the transform domain differ from others by different combinations of transform techniques, it is difficult to decide on an algorithm for a specific application. Therefore, instead of developing a new watermarking algorithm with different combinations of transform techniques, we propose a novel and effective watermark extraction and detection method by pre-filtering, namely Adaptive Unsharp Masking (AUM). In spite of the fact that Unsharp Masking (UM) based pre-filtering is used for watermark extraction/detection in the literature by causing the details of the watermarked image become more manifest, effectiveness of UM may decrease in some cases of attacks. In this study, AUM has been proposed for pre-filtering as a solution to the disadvantages of UM. Experimental results show that AUM performs better up to 11\% in objective quality metrics than that of the results when pre-filtering is not used. Moreover; AUM proposed for pre-filtering in the transform domain image watermarking is as effective as that of used in image enhancement and can be applied in an algorithm-independent way for pre-filtering in transform domain image watermarking

Measure of image enhancement by parameter controlled histogram distribution using color image

Abstract: Histogram Equalization (HE) technique is simple and effectively used for contrast enhancement. But HE is not suitable for consumer electronic products because it may produces washed out appearance image. The new quantitative measures of image enhancement and frequency domain based methods used for object detection and visualization and enhancement technique driven by both global and local process on luminance and chrominance components of the image. This measure of image enhancement is related with the concepts of Weber's law of the human visual systems. It helps to choose the best parameters and transform. This approach based on parameter controlled histogram distribution method can enhance simultaneously overall contrast and sharpness of an image. This approach also increases the visibility of specified portions or better maintaining image color. This analysis provides better performance for contrast enhancement Index terms: Histogram equalization, Image enhancement, Contrast enhancement, I.INTRODUCTION A digital image is converted into analogy signal which is scanned into a display. Before the processing image is converted into digital format, Digitization includes sampling of image and quantization of sampled values. After converting the image into bit, information is processed. In image processing, images are available in digitized form that is arrays of finite length binary format. For digitization, the given images are sampled on a discrete grid and each sample or pixel is quantized using a finite number of bits. The digitized image is used in computer. Image enhancement which transforms digital images to enhance the visual information. To enhance image contrast is the intensity mapping that reassigns the intensity of pixels through a monotonically increasing function. Primary operation for all vision and image processing tasks in several areas. In forensic video/image analysis tasks surveillance videos have quite different qualities compared with other videos such as the videos for high quality entertainment or TV broadcasting. Enhancement transformation to modify the contrast of an image within a display's dynamic range is therefore required in order to show full information content in the videos. Contrast enhancement is an important function in image processing applications. The objective of this method is to make an image clearly recognized for a specific application. Point operation based enhancement techniques are contrast stretching, non-linear point transformation, histogram modeling. The non-linearity is introduced by many imaging lighting device which can be described with a point operation. Gamma correction is using the power law's light intensity operation [1] which is adjusting the lightness/darkness level of their prints. X=(x) (1/gamma value) Where x is the original pixel value. Depending on the gamma value, image can be lightened or darkened. so, it will improve visual contrast and also decreases the visual contrast too. Histogram Equalization (HE) is most popular technique for contrast enhancement. HE makes uniform distribution of the gray level for an image. But, consumer electronics such as Flat panel display (FPD), HE is rarely applied in directly because the significant changes in brightness [2]. The HE effectiveness is depends on the contrast of the original image. In general, HE will flatten out the probability distribution of an image and increase its dynamic range and also will make the average brightness towards the middle gray level of an image regardless of the input image, and produce the objectionable artifacts and unnatural contrast effect. This makes the visual quality of processed image is unsatisfactory. Surveillance videos have quietly different qualities compared with other videos such as videos for high quality entertainment or T