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TMM Featured Articles

JPEG lossy image compression is a still image compression algorithm model that is currently widely used in major network media. However, it is unsatisfactory in the quality of compressed images at low bit rates. The objective of this paper is to improve the quality of compressed images and suppress blocking artifacts by improving the JPEG image compression model at low bit rates.

We have recently seen great progress in image classification due to the success of deep convolutional neural networks and the availability of large-scale datasets. Most of the existing work focuses on single-label image classification. However, there are usually multiple tags associated with an image. The existing works on multi-label classification are mainly based on lab curated labels.

Generating images via a generative adversarial network (GAN) has attracted much attention recently. However, most of the existing GAN-based methods can only produce low-resolution images of limited quality. Directly generating high-resolution images using GANs is nontrivial, and often produces problematic images with incomplete objects.

The scalable video coding extensions of the High Efficient Video Coding (HEVC) standard (SHVC) have adopted a new quadtree-structured coding unit (CU). The SHVC test model (SHM) needs to test seven intermode sizes and one intramode size at depth levels of “0,” “1,” “2,” and four intermode sizes and two intramode sizes at a depth level of “3” for interframe CUs.

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. 

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