Weighted Median (WM) filters have the robustness and edge preserving capability of the classical median filter and resemble linear FIR filters in certain properties. Furthermore, WM filters belong to the broad class of nonlinear filters called stack filters. This enables the use of the tools developed for the latter class in characterizing and analyzing the behavior and properties of WM filters, e.g. noise attenuation capability. The fact that WM filters are threshold functions allows the use of neural network training methods to obtain adaptive WM filters. In this tutorial paper we trace the development of the theory of WM filtering from its beginnings in the median filter to the recently developed theory of optimal weighted median filtering. Applications discussed include: idempotent weighted median filters for speech processing, adaptive weighted median and optimal weighted median filters for image and image sequence restoration, weighted medians as robust predictors in DPCM coding and Quincunx coding, and weighted median filters in scan rate conversion in normal TV and HDTV systems.

Weighted median filters: a tutorial

This paper presents EC feature implemented by the authors in the test model of the draft ITUT video coding standard H.26L.The selected EC algorithms are based on weighted pixel value averaging for INTRA pictures and boundarymatchingbased motion vector recovery for INTER pictures. The specific concealment strategy and some special methods, including handling of Bpictures, multiple reference frames and entire frame losses, are described. Both subjective and objective results are given based on simulations under Internet conditions. The feature was adopted and is now included in the latest H.26L reference software TML9.0.

The Error Concealment Feature in the H.26L Test Model

A method of encoding a video signal for transmission, comprising: receiving a video signal comprising a plurality of video frames, each frame being divided into a plurality of image portions; for each of a plurality of target ones of said image portions to be encoded, selecting a respective reference portion, generating respective residual data based on the target portion relative to the respective reference portion; during ongoing encoding of the video signal, generating a table of commonly usable reference portions and transmitting an indication of the table to a decoder; and generating an encoded bitstream comprising the residual data together with side information identifying the selected reference portions by reference to an entry in said table, and transmitting the encoded bitstream to the decoder.

Data Compression for Video

This paper proposes two data hiding approaches using compressed MPEG video. The first approach hides message bits by modulating the quantization scale of a constant bitrate video. A payload of one message bit per macroblock is achieved. A second order multivariate regression is used to find an association between macroblock-level feature variables and the values of a hidden message bit. The regression model is then used by the decoder to predict the values of the hidden message bits with very high prediction accuracy. The second approach uses the flexible macroblock ordering feature of H.264/AVC to hide message bits. Macroblocks are assigned to arbitrary slice groups according to the content of the message bits to be hidden. A maximum payload of three message bits per macroblock is achieved. The proposed solutions are analyzed in terms of message extraction accuracy, message payload, excessive bitrate and quality distortion. Comparisons with previous work reveal that the proposed solutions are superior in terms of message payload while causing less distortion and compression overhead.

Data Hiding in MPEG Video Files Using Multivariate Regression and Flexible Macroblock Ordering

As the newest video coding standard, high efficiency video coding (HEVC) has great potential as a new information hiding carrier This paper proposes an efficient information hiding method based on motion vector space encoding for HEVC encoding process In this method, the mapping relationship between motion vector set and the points in the motion vector space is defined The motion vector components from the N/2 prediction units (PUs) with smallest size in a coding tree unit (CTU) are selected as the secret information carriers Each N secret bits are converted to a 2N + 1-ary number By modifying at most one element in the set of N motion vector components, the mapping value of the set in the motion vector space can be equal to the 2N + 1-ary number In this way, information hiding is realized Since at most one element is changed and the N/2 PUs with smallest size are selected, this method contributes to excellent transparency of steganography and anti-steganalysis performance with high embedding efficiency To the best of our knowledge, this is the first information hiding method based on motion vector for HEVC Experimental results verify that the proposed method is practicable and has better performance than two typical embedding rules of information hiding based on motion vector

An efficient information hiding method based on motion vector space encoding for HEVC

Data hiding is a type of information hiding technology. A data hiding method based on H.264 encoded video sequences is presented in this paper. The proposed method uses the parity of the coefficients after transformation and quantization to hide the desirable data. The digital data hidden by this approach can be recovered correctly by data recovering process and extracted directly from the encoded stream without using the original host video. Experimental results demonstrate that the proposed method can obtain good performance.

A new method of data hiding based on H.264 encoded video sequences

Sobel operator is widely used to detect the edge direction in most spatial error concealment methods. However, Sobel operator may not work when detecting edge directions in the case of existing line in the image. This paper designs an advanced method of detecting edge directions, which can estimate the direction of both step edge and line correctly. The benefit of the advanced edge detection method is that all edge directions including step edges and lines can be detected properly. The proposed method is applied in a spatial error concealment method. Experimental results show that the advanced method yields better objective and subjective quality than that of using Sobel operator for determining edge direction only.

An Improved Method of Detecting Edge Direction for Spatial Error Concealment

The discrete cosine transform (DCT) is widely used in image/video coding standards. However, since most DCT coefficients will be quantized to zeros, a large number of redundant computations are introduced. This paper presents an early detection algorithm to predict zero-quantized DCT coefficients for fast JPEG encoding. Based on the theoretical analysis for 2-D DCT and quantization in JPEG standard, we derive a sufficient condition under which each quantized coefficient becomes zero. Finally, the transform of the zero-quantized coefficients is omitted. Experimental results show that the proposed algorithm can significantly reduce the redundant computations and speed up the image encoding. Moreover, it doesn't cause any performance degradation. Computational reduction also implies longer battery lifetime and energy economy for digital applications.

A detection algorithm for zero-quantized DCT coefficients in JPEG

Almost all variable length 3D-DCT algorithms employ thresholds. Although the selection of threshold considerably affects the algorithm performance, there is no framework to choose them effectively. This paper proposes a hybrid transform for 3D-DCT based video coding. In the proposed model, 3D-DCT and discrete Haar transform are iteratively used to remove the redundancy for each cube and thus an adaptive scheme is derived to realize variable temporal length of DCT implementations. Compared to other methods in the literature, the proposed model can mathematically select the optimal DCT mode and remove the temporal correlations more effectively. Experimental results show that the proposed approach has substantial improvement over the conventional fixed-length 3D-DCT coding and other variable length 3D-DCT coding.

Variable temporal length 3D DCT-DWT based video coding

Change detection in images of a given scene acquired at different times is one of the most interesting topics of remote image processing. In this paper, a novel image change detection algorithm is proposed based on the clustering characteristic of 2-D histogram. First, the best segmentation direction of 2-D histogram is ascertained by using Fisher criterion. Secondly, a kind of new 2-D entropy is defined to search the best threshold and segment the 2-D histogram into unchanged region and change region. Then the change area in different image is detected based on the change region of 2-D histogram. Finally, the proposed algorithm is compared to traditional algorithm. The theoretical analysis and experiment results confirm the effectiveness of the proposed means.

Research of unsupervised image change detection algorithm based on 2-D histogram

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