An encoding device includes a color component separating unit for separating an input bit stream for the respective color components, a block dividing unit for dividing an input color component signal into blocks to generate a signal of an encoding unit area, a predicted image generating unit for generating a predicted image for the signal, a determining unit for determining a prediction mode used for encoding according to a prediction efficiency of the predicted image, a prediction error encoding unit for encoding a difference between the predicted image corresponding to the prediction mode determined by the determining unit and the input color component signal, and an encoding unit for variable length-coding the prediction mode, an output from the prediction error encoding unit, and a color component identification flag indicating the color component to which the input bit stream belongs as a result of the color component separation.

Image encoding device, image decoding device, image encoding method, and image decoding method

An apparatus includes a display control unit, including a processor, configured to control a display to display a plurality of objects and receive a selection of one of the plurality of objects by a user as a selected object. The display control unit is configured to control the display to move the selected object when a move command is received from the user. The display control unit is configured to control the display to group additionally selected objects with the selected object when additional objects are selected by the user and a group command is received from the user. The display control unit is configured to control the display to independently move the additionally selected objects with respect to the selected object until the additionally selected objects are grouped with the selected object.

Information processing apparatus, information processing method, and information processing program

Most saliency estimation methods aim to explicitly model low-level conspicuity cues such as edges or blobs and may additionally incorporate top-down cues using face or text detection. Data-driven methods for training saliency models using eye-fixation data are increasingly popular, particularly with the introduction of large-scale datasets and deep architectures. However, current methods in this latter paradigm use loss functions designed for classification or regression tasks whereas saliency estimation is evaluated on topographical maps. In this work, we introduce a new saliency map model which formulates a map as a generalized Bernoulli distribution. We then train a deep architecture to predict such maps using novel loss functions which pair the softmax activation function with measures designed to compute distances between probability distributions. We show in extensive experiments the effectiveness of such loss functions over standard ones on four public benchmark datasets, and demonstrate improved performance over state-of-the-art saliency methods.

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End-to-End Saliency Mapping via Probability Distribution Prediction

A video encoder may transform residual data by using a transform selected from a group of transforms. The transform is applied to the residual data to create a two-dimensional array of transform coefficients. A scanning mode is selected to scan the transform coefficients in the two-dimensional array into a one-dimensional array of transform coefficients. The combination of transform and scanning mode may be selected from a subset of combinations that is based on an intra-prediction mode. The scanning mode may also be selected based on the transform used to create the two-dimensional array. The transforms and/or scanning modes used may be signaled to a video decoder.

Video coding using mapped transforms and scanning modes

Several implementations relate, for example, to depth encoding and/or filtering for 3D video (3DV) coding formats. A sparse dyadic mode (308) for partitioning macroblocks (MBs) along edges in a depth map is provided as well as techniques for trilateral (or bilateral) filtering of depth maps that may include adaptive selection between filters sensitive to changes in video intensity and/or changes in depth. One implementation partitions a depth picture, and then refines the partitions based on a corresponding image picture. Another implementation filters a portion of a depth picture based on values for a range of pixels in the portion. For a given pixel in the portion that is being filtered, the filter weights a value of a particular pixel in the range by a weight that is based on one or more of location distance, depth difference, and image difference.

Method and devices for depth map processing

When for video coding Intra refresh is used, which inserts Intra coded blocks into previously Inter coded pictures, an efficiently adapted rate control method is required for error resilient video coding. A method for adaptively determining a bit budget for encoding video pictures comprises pre-analyzing (31) each of the pictures of a group of pictures, wherein a relative complexity index (35) is calculated for each picture, allocating (32) bits to the pictures based on their relative complexily index (35) and encoding (33, 34) each of the pictures with the allocated number of bits. The pre-analysis (31) comprises selecting (42) pictures for Intra refresh coding, extracting (41) attention area information (47) from the selected pictures, encoding at least the macroblocks of the attention area using Intra mode, calculating for each picture a complexity index (44), and calculating from the complexity indices (44) of the pictures of the group a relative complexity index (35) for each picture. Thus, a subjectively better video quality is achieved.

Method and apparatus for adaptively determining a bit budget for encoding video pictures

The present invention provides a salience estimation method for object-based visual attention model. The method comprises steps of segmenting the image into a plurality of objects to be estimated, extracting feature maps for each segmented object, calculating the saliences of each segmented object in a set of circles defined around a centre pixel of the object based on the extracted feature maps, and integrating the saliences of each segmented object in all circles in order to achieve an overall salience estimation for each segmented object. The present invention is much more human vision inosculated and of low computing complexity.

Salience estimation for object-based visual attention model

The frame following a scene cut is usually coded as an I picture. In CBR encoding, the encoder will try to keep the bit rate constant, which will often cause serious picture quality degradation at scene changes. In VBR encoding, more bits will be allocated to the first frame of the new scene and the bit rate will increase significantly for a short time. Therefore subsequent frames must be coded in ‘skipped’ mode, which will often cause jerk artifacts. According to the invention, in each frame belonging to a scene change period, areas are determined that have different human attention levels. In the frames (n−1, n−2, n−3) located prior to the first new scene frame, to the areas having a lower attention level less bits are assigned than in the default encoding, and in the frames (n, n+1, n+2) located at and after the scene cut the thus saved bits are additionally assigned to the areas having a higher attention level.

Method and apparatus for adapting a default encoding of a digital video signal during a scene change period

Optimised bit allocation is important in video compression to increase the coding efficiency, i.e. to make optimum use of the available data rate. In view of the human visual system, a human usually pays more attention to some part of a picture rather than to other parts of that picture. Therefore the bit allocation should be optimised for different-attention picture areas (GOBi). The inventive distortion-driven bit allocation scheme allocates the coding/decoding error distortion to picture areas consistently with the human visual system, and satisfies the constraint of bit rate as well. The invention uses a distortion/bitrate/rhoquantisation parameter histogram analysis. Based on corresponding tables (DGOBi[QPn], RGOBi[QPn] and ρGOBi[QPn]), the relationships between quantisation parameter, rate, distortion and percentage of non-zero coefficients for the different-attention areas are determined (PREALUTI, DISALL, RALL). Thereafter a rho-domain bit rate control is used (RDBALL) for calculating the bit allocation inside each group of macroblocks.

Method and apparatus for determining in picture signal encoding the bit allocation for groups of pixel blocks in a picture

Image or video encoding standards provide different intra prediction modes, which may employ a spatial intra prediction direction and a DFT. Picture encoding is further optimized by an adaptive quantization of the frequency domain parameters. A method for quantizing or inverse quantizing frequency domain parameters that refer to a residual, which is the difference between a current image and a predicted image, is disclosed. If the predicted image was obtained by spatial intra prediction (10) using an intra-prediction direction, one of a plurality of different quantization matrices is selected (14) and used for quantizing (13) or inverse quantizing said parameters. The selection depends on the intra-prediction direction (s10) that was used. As a result, for images with horizontal prediction direction the quantization is finer for horizontal structures than for vertical structures, and vice versa. Advantageously, no extra header bits need to be introduced to indicate the de-quantization matrices.

Xiao Dong Gu

Papers

Method and apparatus for adaptively determining a bit budget for encoding video pictures

Salience estimation for object-based visual attention model

Method and apparatus for adapting a default encoding of a digital video signal during a scene change period

Method and apparatus for determining in picture signal encoding the bit allocation for groups of pixel blocks in a picture

Method and device for adaptively quantizing parameters for image coding