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.

Event multiplexer for managing the capture of images

Abstract: An image capture system for capturing images of an object, such as the Earth. The image capture system includes a moving platform, at least two image capture devices, a position system, an event multiplexer and a computer system. The image capture devices are mounted to the moving platform. Each image capture device has a sensor for capturing an image and an event channel providing an event signal indicating the capturing of an image by the sensor. The position system records data indicative of a position as a function of time related to the moving platform. The event multiplexer has at least two image capture inputs and at least one output port. Each image capture input receives event signals from the event channel of one of the image capture devices. The event multiplexer outputs information indicative of an order of events indicated by the event signals, and identification of image capture devices providing the event signals. The computer system receives and stores the information indicative of the order of events indicated by the event signals, and identification of image capture devices providing the event signals.

A digital secure image communication scheme based on the chaotic Chebyshev map

Abstract: In this paper, a simple image secure communication scheme based on the chaotic Chebyshev map and chaos synchronization is proposed. The scheme relies on the excellent correlation property of chaotic sequences, which is very desirable for secure image communication. The results obtained by computer simulation indicate that the transmitted source image can be correctly and reliably recovered using the proposed scheme, even through a noisy channel. Notably, the scheme possesses relatively high security and can be easily implemented. Moreover, the quality of the recovered image is satisfactory, quantified by such common criteria as the bit-error rate performance. Copyright © 2004 John Wiley & Sons, Ltd.

Removing ringing and blocking artifacts from JPEG compressed document images

Abstract: A method of removing ringing and blocking artifacts from a decompressed digital image. In one method, a background value of the digital image a background region and foreground regions is determined, and a threshold value is computed. A mapping of the digital image is then generated by thresholding the digital image based on the threshold value to produce a thresholded image, and enlarging the foreground regions of the thresholded image to form a map image. The mapping includes the background pixels of the map image. The background region of the decompressed digital image is then cleansed based on the mapping. In an alternate method, ringing artifacts are removed from a decompressed digital image based on a signal-to-noise ratio of the image. In yet another alternate embodiment, ringing artifacts are from a decompressed digital color image that includes a chrominance channel and a luminance channel. An alternate embodiment removes ringing and blocking artifacts.

Quaternion Locality-Constrained Coding for Color Face Hallucination

Abstract: Recently, the locality linear coding (LLC) has attracted more and more attentions in the areas of image processing and computer vision. However, the conventional LLC with real setting is just designed for the grayscale image. For the color image, it usually treats each color channel individually or encodes the monochrome image by concatenating all the color channels, which ignores the correlations among different channels. In this paper, we propose a quaternion-based locality-constrained coding (QLC) model for color face hallucination in the quaternion space. In QLC, the face images are represented as quaternion matrices. By transforming the channel images into an orthogonal feature space and encoding the coefficients in the quaternion domain, the proposed QLC is expected to learn the advantages of both quaternion algebra and locality coding scheme. Hence, the QLC cannot only expose the true topology of image patch manifold but also preserve the inherent correlations among different color channels. Experimental results demonstrated that our proposed QLC method achieved superior performance in color face hallucination compared with other state-of-the-art methods.