IEEE TMM Article

Using deep convolutional neural networks (CNN) to predict the depth from a single image has received considerable attention in recent years due to its impressive performance. However, existing methods process each single image independently without leveraging the multiview information of video sequences in practical scenarios.

Image decolorization is a task aiming to transform a color image to a grayscale one and is a dimension reduction process which inevitably suffers from information loss. The general goal of image decolorization is to preserve the color contrast of the color image. According to human visual study, exposure affects the human visual perception, and low-exposure areas or over-exposure areas will first attract the sense of sight.

Watermarking plays an important role in identifying the copyright of an image and related issues. The state-of-the-art watermark embedding schemes, spread spectrum and quantization, suffer from host signal interference (HSI) and scaling attacks, respectively. Both of them use a fixed embedding parameter, which is difficult to take both robustness and imperceptibility into account for all images.

Screen content coding (SCC) is the extension to high-efficiency video coding (HEVC) for compressing screen content videos. New coding tools, intrablock copy (IBC), and palette (PLT) modes, are introduced to encode screen content (SC) such as texts and graphics. The IBC mode is used for encoding repeating patterns by performing block matching within the same frame, while the PLT mode is designed for SC with few distinct colors by coding the major colors and their corresponding locations using an index map.

In past years, various encrypted algorithms have been proposed to fully or partially protect the multimedia content in view of practical applications. In the context of digital TV broadcasting, transparent encryption only protects partial content and fulfills both security and quality requirements. 

This paper presents a new method of secret three-dimensional object sharing (S3DOS), which allows sharing of three-dimensional (3-D) objects, while preserving its file format by selectively encrypting a 3-D object in order to sufficiently protect the visual nature of the content. 

This paper addresses the problem of encoding the video generated by the screen of an airplane cockpit. As other computer screens, cockpit screens consist of computer-generated graphics often atop a natural background. Existing screen content coding schemes fail notably in preserving the readability of textual information at the low bitrates required in avionic applications. 

In this paper, we propose a coding tree unit (CTU)-level rate control scheme from the perspective of SSIM-based rate-distortion optimization to improve the coding efficiency. First, we establish the SSIM-based rate-distortion model based on the divisive normalization scheme, which characterizes the relationship between the local visual quality and the coding bits.

With the rapid popularization of mobile intelligent terminals, mobile video and cloud services applications are widely used in people's lives. However, the resource-constrained characteristic of the terminals and the enormous amount of video information make the efficient terminal-to-cloud data upload a challenge.

Multimedia streams consume a significant chunk of the consumer Internet traffic exchanged and will continue to do so due to the ever-increasing connection among people, businesses, and industries. To cope with the deviation of the Internet's intended use, unreliable underlying infrastructure, and best effort protocols while leveraging existing technologies...