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In this paper, we propose a rate adaptive compressed sensing for block-based DCVS framework, in which the sampling rate is estimated at the decoder side and can be sent back to the encoder via the return channel. The assignment of measurements rate (MR) is depending on the variance of the residual measurements between SI and the reconstructed CS frame. By comparing with the encoder-based scheme, the...
Steganography is the art of concealing information within different types of media objects such as images or audio files. Its counterpart, Steganalysis, is the study of methods that uncover information in a suspicious file, which has being altered for stego purposes. Its techniques rely on the inspection of changes at the pixel information level. In this paper, we propose a method for Secret-key Steganography...
The compressed sensing (CS) theory shows that a sparse signal can be recovered at a sampling rate that is (much) lower than the required Nyquist rate. In practice, many image signals are sparse in a certain domain, and because of this, the CS theory has been successfully applied to the image compression in the past few years. The most popular CS-based image compression scheme is the block-based CS...
Prediction based algorithms reported in the literature are not able to integrate lossy and near-lossless/lossless coding and uses only causal pixels (non-symmetrical predictor structure) for prediction. A non-symmetrical predictor structure, however, is not able to efficiently adapt near the intensity varying areas, which results into poor prediction. Hence, we propose a novel two-stage algorithm...
In this paper the problem of decoder side error concealment is considered. A comparison of several restoration methods is presented. All the compared methods belong to the class of exemplar based inpainting algorithms. It is shown that patch based methods are effective for restoration of small macroblocks while block based methods are effective for restoration of large macroblocks.
The standard Compressive Sensing (CS) theory indicates that robust signals recovery can be obtained from just a few collection of incoherent projections. To further decrease the necessary measurements, an alternative to the generic CS framework assumes that signals lie on a union of subspaces (UoS). However, UoS model is limited to the specific type of signal regularity. This paper considers a more...
In this paper, an effective multiple description image coding technique is developed to achieve competitive coding efficiency at low encoder complexity, while being standard compliant. The new technique is particularly suitable for visual communication over packet-switched networks and with resource-deficient wireless devices. To keep the encoder simple and standard compliant, multiple descriptions...
Conventional image and video communication systems are usually designed with the objective being to maximize the fidelity of reconstructed images measured by mean square errors (MSE). It is well known that the fidelity metric MSE may not reflect the visual quality perceived by human eyes. Recent advancements in image quality assessment tell us that the structural similarity (SSIM), especially the...
This paper proposes a new two-dimensional antidictionary coding for a given rectangle. An antidictionary is the set of all the minimal forbidden rectangles for an input rectangle. The proposed encoder outputs a pair of an antidictionary and a unique polyomino which appears only once in an input rectangle as a codeword. The input rectangle can be decoded from the pair. Both the encoding and decoding...
We design a video coding and decoding framework for multi-view video systems based on compressed sensing imaging principles. Specifically, we focus on joint decoding of independently encoded compressively-sampled multi-view video streams. We first propose a novel distributed coding/decoding architecture designed to leverage inter-view correlation through joint decoding of the received compressively-sampled...
A common practice in low bit-rate image/video compression is uniform spatial down-sampling at the encoder and upsampling at the decoder. The down-sampling is performed in conjunction with deterministic low-pass filtering (e.g., Gaussian or the alike) to prevent aliasing. The down-sampled image is compressed and decompressed as usual; the upsampling is treated as an image restoration problem. In this...
In this paper, we propose a representation and coding method for multiview images. As an alternative to depth-based schemes, we propose a representation that captures the geometry and the dependencies between pixels in different views in the form of connections in a graph. In our approach it is possible to perform compression of the geometry information and to preserve a direct control of the effect...
Compressive sensing (CS) provides a general signal acquisition framework that enables the reconstruction of sparse signals from a small number of linear measurements. To reduce video-encoder complexity, we present a CS-based video compression scheme. Modern video-encoder complexity arises mainly from the transform-coding and motion-estimation blocks. In our proposed scheme, we eliminate these blocks...
In memory design, people have conventionally assumed that all bit-cells have same importances and hence, made many efforts to obtain memory free from bit-cell failures. However, such an assumption may not be true in video applications such as H.264 and MPEG-4. Here, higher order bits of luminance pixels can be considered more critical compared to lower order bits. It is due to the fact that human...
A novel watermarking scheme is proposed for up-sampling based multiple description coding frame in this paper. Secret information is embedded in the DWT image. Up-sampling algorithm is applied on transformed image to introduce some redundancy between different channels. Good performance of the new frame to against noise and to resist the compression attacks is shown in the experimental results.
Recently, Tso proposed an efficient (k, n) secret image sharing scheme (SISS) based on Blakley's secret sharing, to share a secret image into n shadow images. One can decode a secret image with any k or more than k shadow images, but cannot obtain any information about the secret from less than k shadow images. With the help of quantization, Tso's (k, n)-SISS can reduce the storage space. However,...
In wireless video multicast, the main challenge is to meet the demands of heterogeneous receivers who face the same video source stream but show different channel characteristics. This paper proposes an improved compressed-sensing-base wireless video multicast (iCS-WVM) technique, where the measurements of each group of pictures (GOP) are packed and transmitted through an analog channel. Each receiver...
Compressive Sensing (CS) suggests that, under certain conditions, a signal can be reconstructed using a small number of incoherent measurements. We propose a novel video CS framework based on Multiple Measurement Vectors (MMV) which is suitable for signals with temporal correlation such as video sequences. In addition, a CS circulant matrix is employed for fast reconstruction. Furthermore, the proposed...
A method for the progressive lossy-to-lossless coding of arbitrarily-sampled image data is proposed. Through experimental results, the proposed method is demonstrated to have a rate-distortion performance that is vastly superior to that of the state-of-the-art image-tree (IT) coding scheme. In particular, at intermediate rates (i.e., in progressive decoding scenarios), the proposed method yields image...
In this paper, we consider an undersampling system model of the form y = A(T(x, θ)) + n, where x is a k-sparse signal, T(·, · is a (possibly non-linear) function specified by a parameter vector θ and acting on x, A is a sensing matrix, and n is additive measurement noise. We consider an information theoretic decoder that aims to recover the sparse signal and the transformation parameter vector jointly,...
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