Channel (digital image)

About: Channel (digital image) is a research topic. Over the lifetime, 7211 publications have been published within this topic receiving 69974 citations.

A novel image authentication scheme based on hyper-chaotic cell neural network

Abstract: This paper presents a new image authentication scheme based on cell neural network with hyper-chaos characteristics (HCCNN). In the scheme, the authentication code, which is used as secret key and the pixel values of image are used for the input of HCCNN. The secret information that HCCNN produces is transmitted to the receiving end through secret channel. The receiver can then use the received secret information to authenticate the suspect image by comparing the original authentication code with that calculated from the suspect image. Simulations show that the suggested image authentication algorithm has the advantages of large key space and high security, and moreover, it can detect and locate the position of any slightly tampered parts of a suspect image.

Underwater image restoration by red-dark channel prior and point spread function deconvolution

Abstract: In the field of undersea research, underwater vehicles usually carry camera systems for recording. The captured image or video often has two undesired characteristics: color distortion and low visibility. This is because that the light is exponentially attenuated while penetrating through water. Furthermore, the quality of attenuation is associated with the wavelength of spectrum. This paper simplifies the Jaffe-McGlamery optical model and proposes an effective algorithm to recover underwater images. In our approach, a red-dark channel prior was defined and derived to estimate the background light and the transmission. The visibility of scene was compensated by the object-camera distance to recover the colors of the background and objects. Subsequently, by analyzing the physical property of the point spread function, we developed a simple but efficient low-pass filter to deblur degraded underwater images. A wide variety of underwater images with different scenarios were used for the experiments. The experimental results indicated that the proposed algorithm effectively recovered underwater images while eliminating the influence of absorption and scattering. We believe that this new restoration algorithm is promising in many underwater image processing applications.

Shadow detection in color aerial images based on HSI space and color attenuation relationship

Abstract: Many problems in image processing and computer vision arise from shadows in a single color aerial image. This article presents a new algorithm by which shadows are extracted from a single color aerial image. Apart from using the ratio value of the hue over the intensity in some state-of-the-art algorithms, this article introduces another ratio map, which is obtained by applying the saturation over the intensity. Candidate shadow and nonshadow regions are separated by applying Otus’s thresholding method. The color attenuation relationship that describes the relationship between the attenuation of each color channel is derived from the Planck’s blackbody irradiance law. For each region, the color attenuation relationship and other determination conditions are performed iteratively to segment it into smaller sub-regions and to identify whether each sub-region is a true shadow region. Compared with previous methods, the proposed algorithm presents better shadow detection accuracy in the images that contain some dark green lawn, river, or low brightness shadow regions. The experimental results demonstrate the advantage of the proposed algorithm.

Rolling-shutter-effect camera-based visible light communication using RGB channel separation and an artificial neural network

Abstract: We propose and demonstrate a light-panel and rolling-shutter-effect (RSE) camera-based visible light communication (VLC) system using Z-score normalization, red/green/blue (RGB) color channel separation, and 1-D artificial neural network (ANN). The proposed scheme can mitigate the high inter-symbol interference (ISI) generated by the RSE pattern due to the low pixel-per-bit and high noise-ratio (NR) of the display contents.

Human action recognition method based on two-channel infrared information fusion

Abstract: The invention discloses a human action recognition method based on two-channel infrared information fusion, and the method comprises the following steps of: collecting a human motion video image through an infrared camera, and collecting a human motion voltage signal through a pyroelectric infrared sensor; respectively carrying out feature extraction on the collected human motion video image and human motion voltage signal, wherein human contour energy is obtained from the human motion video image and spectrum signature is obtained from the human motion voltage signal; respectively carrying out principal component analysis on the human contour energy and the spectrum signature; fusing the principal component analysis results on a feature layer; and carrying out classification and identification on the fused features through the support vector machine method combined with corresponding data in the human infrared action data base. According to the method, multi-level human action information in the infrared image is fully utilized and the human direction information in the output signals of the pyroelectric infrared sensor is fused so as to realize classification and identification on different human actions in different directions and ensure accurate action recognition rate.