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.

Digital broadcast receiving method providing two-dimensional image and 3d image integration service, and digital broadcast receiving device using the same

Abstract: A digital broadcast receiving apparatus for providing an integrated service of a 2D image and a 3D image comprises: a demultiplexing unit configured to demultiplex a received digital broadcast signal; a PSIP or PSI/SI processor configured to extract at least any one of 3D service information related to a 2D image channel or service and 2D service information related to a 3D image channel or service from the demultiplexed digital broadcast signal; a decoder configured to decode an extension view video stream and a base view video stream from the demultiplexed digital broadcast signal; and an output formatting unit configured to format the extension view video stream and the base view video stream based on at least any one of the 3D service information and the 2D service information. When a selection of the 3D image service is input by a user, a 3D image channel or service providing a 3D image with respect to the 2D image channel or service based on the 3D service information may be selected, and when a selection of the 2D image service is input by the user, a 2D image channel or service providing a 2D image with respect to the 3D image channel or service based on the 2D service information may be selected. Accordingly, an integrated service of a 2D image and a 3D image can be provided in a digital broadcast.

Estimation of the radiometric response functions of a color camera from differently illuminated images

Abstract: The mapping that relates the image irradiance to the image brightness (intensity) is known as the Radiometric Response Function or Camera Response Function. This usually unknown mapping is nonlinear and varies from one color channel to another. In this paper, we present a method to estimate the radiometric response functions (of R, G and B channels) of a color camera directly from the images of an arbitrary scene taken under different illumination conditions (The illumination conditions are not assumed to be known). The response function of a channel is modeled as a gamma curve and is recovered by using a constrained nonlinear minimization approach by exploiting the fact that the material properties of the scene remain constant in all the images. The performance of the proposed method is demonstrated experimentally.

Evaluation of Feature Channels for Correlation-Filter-Based Visual Object Tracking in Infrared Spectrum

Abstract: Correlation filters for visual object tracking in visible imagery has been well-studied. Most of the correlation-filterbased methods use either raw image intensities or feature maps of gradient orientations or color channels. However, well-known features designed for visible spectrum may not be ideal for infrared object tracking, since infrared and visible spectra have dissimilar characteristics in general. We assess the performance of two state-of-the-art correlationfilter-based object tracking methods on Linkoping Thermal InfraRed (LTIR) dataset of medium wave and longwave infrared videos, using deep convolutional neural networks (CNN) features as well as other traditional hand-crafted descriptors. The deep CNN features are trained on an infrared dataset consisting of 16K objects for a supervised classification task. The highest performance in terms of the overlap metric is achieved when these deep CNN features are utilized in a correlation-filter-based tracker.

A Novel Color Image Encryption Algorithm Based on Hyperchaotic Maps and Mitochondrial DNA Sequences

Abstract: Multimedia encryption innovation is one of the primary ways of securely and privately guaranteeing the security of media transmission. There are many advantages when utilizing the attributes of chaos, for example, arbitrariness, consistency, ergodicity, and initial condition affectability, for any covert multimedia transmission. Additionally, many more benefits can be introduced with the exceptional space compliance, unique information, and processing capability of real mitochondrial deoxyribonucleic acid (mtDNA). In this article, color image encryption employs a confusion process based on a hybrid chaotic map, first to split each channel of color images into n-clusters; then to create global shuffling over the whole image; and finally, to apply intrapixel shuffling in each cluster, which results in very disordered pixels in the encrypted image. Then, it utilizes the rationale of human mitochondrial genome mtDNA to diffuse the previously confused pixel values. Hypothetical examination and trial results demonstrate that the anticipated scheme exhibits outstanding encryption, as well as successfully opposes chosen/known plain text, statistical, and differential attacks.

Color Channel Transfer for Image Dehazing

Abstract: In this letter we introduce a simple but effective concept, Color Channel Transfer (CCT), that is able to substantially improve the performance of various dehazing techniques. CCT is motivated by a key observation: in scattering media the information from at least one color channel presents high attenuation. To compensate for the loss of information in one color channel, CCT employs a color-transfer strategy and operates in a color opponent space that helps to compensate automatically the chromatic loss. The reference is computed by combining the details and saliency of the initial image with uniform gray image that assures a balanced chromatic distribution. The extensive qualitative and quantitative experiments demonstrate the utility of CCT as a preprocessing step for various dehazing problems such as day-time dehazing, night-time dehazing, and underwater image dehazing.