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

In weak-light environments, images suffer from low contrast and the loss of details. Traditional image enhancement models are usually failure to avoid the issue of overenhancement. In this paper, a simple and novel correction method is proposed based on an adaptive local gamma transformation and color compensation, which is inspired by the illumination reflection model. Our proposed method converts the source image into YUV color space, and the Y component is estimated with a fast guided filter. The local gamma transform function is used to improve the brightness of the image by adaptively adjusting the parameters. Finally, the dynamic range of the image is optimized by a color compensation mechanism and a linear stretching strategy. By comparing with the state-of-the-art algorithms, it is demonstrated that the proposed method adaptively reduces the influence of uneven illumination to avoid overenhancement and improve the visual effect of low-light images.

Underwater image enhancement algorithm based on dark channel prior and underwater imaging model

The main reason for the degradation of the underwater image is the light absorption and scattering. The images are captured in the underwater environment often have some problems such as loss of image information, low contrast, and color distortion. In order to solve the above problems, this paper proposes an image enhancement method for the underwater environment. With the help of the underwater imaging model and dark channel prior theory, a new idea of adding transmission correction and color compensation to G and B color channels is proposed. Experimental results show that, compared with the traditional methods, this method has a better effect on the underwater image with less color deviation.

Visible and Near-Infrared Image Synthesis Using PCA Fusion of Multiscale Layers

This study proposes a method of blending visible and near-infrared (NIR) images to enhance their edge details and local contrast based on the Laplacian pyramid and principal component analysis (PCA). In the proposed method, both the Laplacian pyramid and PCA are implemented to generate a radiance map. Using the PCA algorithm, the soft-mixing method and the mask-skipping filter were applied when the images were fused. The color compensation method uses the ratio between the radiance map fused by the Laplacian pyramid and the PCA algorithm and the luminance channel of the visible image to preserve the chrominance of the visible image. The results show that the proposed method improves edge details and local contrast effectively.

Color compensation in anomalous trichromats assessed with fMRI

Anomalous trichromacy is a common form of congenital color-deficiency resulting from a genetic alteration in the photopigments of the eye’s light receptors. The changes reduce sensitivity to reddish and greenish hues, yet previous work suggests that these observers may experience the world to be more colorful than their altered receptor sensitivities would predict, potentially indicating an amplification of post-receptoral signals. However, past evidence suggesting such a gain adjustment rests on subjective measures of color appearance or salience. We directly tested for neural amplification by using fMRI to measure cortical responses in color-anomalous and normal control observers. Color contrast response functions were measured in two experiments with different tasks to control for attentional factors. Both experiments showed a predictable reduction in chromatic responses for anomalous trichromats in primary visual cortex. However, in later areas V2v and V3v, chromatic responses in the two groups were indistinguishable. Our results provide direct evidence for neural plasticity that compensates for the deficiency in the initial receptor color signals and suggest that the site of this compensation is in early visual cortex.

Study on the Color-Compensation Effect of Composite Orange-Red Quantum Dots in WLED Application

Quantum dots (QDs) as emerging light-converting materials show the advantage of enhancing color quality of white light-emitting diode (WLED). However, WLEDs employing narrow-emitting monochromic QDs usually present unsatisfactory color rendering in the orange region. Herein, composite orange-red QDs (composite-QDs) are developed through mixing CdSe/ZnS based orange QDs (O-QDs) and red QDs (R-QDs) to compensate the orange-red light for WLEDs. We investigated the effect of self-absorption and fluorescence resonance energy transfer (FRET) process in composite-QDs on the spectral controllability and fluorescent quenching in WLEDs. The concentration and donor/acceptor ratios were also taken into account to analyze the FRET efficiency and help identify suitable composite-QDs for color compensation in the orange-red light region. As the result, the optimized composite-QDs effectively improve the color rendering index of the WLED compared with monochromatic QDs.