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This papers deals with an efficient image compression technique for images having low dynamic range. The images with low dynamic range generally have low intensity variations. By considering this fundamental characteristic into account we can go for image compression at higher ratio with small modifications to the existing block based EZW algorithm. To achieve the improvement in compression ratio,...
If a region is semantically more important than others, it is appropriate that a image compression scheme is capable of handling the regional semantic difference because the information loss of the interested region is more severe. We propose the quality scalable coding with its model by introducing the quality scale parameter. It is more extended and generalized image compression philosophy than...
This paper addresses the patch size issue in sparse representation over learned dictionaries. A strategy for selecting the best patch size is proposed. It is empirically shown that the representation quality of natural image patches depends on the patch size considered. The proposed strategy selectively chooses the most appropriate patch size based on the resulting sparse representation error. The...
The proposed work develops an efficient multi spectral band imagery compression technique using adaptive haar wavelet transform, called tetrolet transform. Geometrical features are most important prominent factor in multispectral image processing. But existing compression algorithms are fail to preserve geometrical features at high compression ratio, which implicates the visual cognitive effects around...
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...
Vector quantization (VQ) is a simple and useful data compression algorithm which has been widely applied in many fields such as image processing and pattern recognition. Because each data block is encoded by only one approximate vector in the codebook, the accuracy of the reconstructed blocks is usually poor in VQ. In this paper, the bilinear vector quantization (BVQ) algorithm is proposed with simple...
A multiple description coding scheme based on prediction-induced randomly offset quantizers is proposed, where each description encodes one source subset with a small quantization stepsize, and other subsets are predictively coded with a large quantization stepsize. Due to the prediction, the quantization bins that a coefficient belongs to in different descriptions are randomly overlapped with each...
Multiple Description Coding (MDC) is a useful source coding method for concealing error in lossy networks. Network coding (NC) permits intermediate nodes within a network to apply algebraic mathematic process on independent streams in transmitter and receiver. This paper attempts to protect data and conceal errors happen in the network by joining MDC and p-cycle NC. First, input data (image) is zero...
According to the relationship between matching mean square error and ortho difference sum, range can find the best matching defined-domain within the narrower scope of search. At the same time, the defined-domain having smaller standard deviation will be excluded within the entire codebooks previously and all the ranges having smaller standard deviation will be substituted by their mean values during...
Compressed Sensing (CS) enables magnetic resonance imaging (MRI) at high undersampling by exploiting the sparsity of MR images in a certain transform domain or dictionary. Recent approaches adapt such dictionaries to data. While adaptive synthesis dictionaries have shown promise in CS based MRI, the idea of learning sparsifying transforms has not received much attention. In this paper, we propose...
Holography is deemed the ultimate 3D [1]. Holographic displays provide full eye accommodation, thus not causing eye strain or headaches which are an inconvenient side-effect of 3D stereo [2][3]. As the etymological meaning of Holography suggests, digital holograms store full 3D information of the recorded object (including multiple views). For that reason, storage and transmission of digital holographic...
In this paper, we present a method to perform a digitalspace transmission of an interference fringe-type computergenerated hologram using IrSimple. IrSimple was defined by IrDA technical standard, and it was developed for the purpose of sending image data at high speed using an infrared-rays. We performed infrared digital transmission using IrSimple, and we minimized the size of the transmitted file...
Data confidentiality is a critical issue in today¡¦s computing environment. When data are exchanged via ubiquitous computing devices, they become even more vulnerable to malicious people since eavesdropping are easy. Data hiding, a technique to hide data into cover media, can reduce the risks of eavesdropping. In this paper, we propose a steganographic scheme based on vector quantization (VQ) that...
Integral Imaging (InIm) is a promising three-dimensional (3D) content creation and delivery technique. The simplicity of the method constitutes a straightforward and compact way for acquiring and displaying 3D data. However issues like integrity and authentication of a transmitted InIm are not discussed in the literature. In this paper we propose a jointly optimized InIm fragile self watermarking...
Videos are often required to be transmitted over different media. Scalability is an important aspect of video transmission. In case of challenged network, graceful reconstruction from a truncated bitstream becomes an issue. In order to leverage capabilities of standard video codecs, we suggest our scalable coding through a wrapper on top of any Commercial Off-the-Shelf (COTS) codecs. A single video...
Encoding data based on binary encoding methods and visual cryptography schemes is presented in this paper. First, a visual cryptography scheme is used to share pixels of a covert data to form two shadow matrices by using a specified sharing matrix. Then, the two shadow matrices are encoded into a host image to form an overt image by using a specific encoding rule. The overt image contains four groups...
During Coefficient thresholding (CT), the last several nonzero DCT coefficients after quantization are dropped if better Rate-Distortion (RD) performance can be achieved. Since image data can be reconstructed by incomplete frequency information with some prior knowledge of image property (e.g., luminance continuity), the quality degradation caused by CT can be sometimes alleviated by some prior knowledge...
The problem of learning a data-adaptive dictionary for a very large collection of signals is addressed. This paper proposes a statistical model and associated variational Bayesian (VB) inference for simultaneously learning the dictionary and performing sparse coding of the signals. The model builds upon beta process factor analysis (BPFA), with the number of factors automatically inferred, and posterior...
A scalable multiple description scalar quantizer (SMDSQ) is a quantization based framework used for scalable multiple description coding (SMDC). In this paper, we introduce a novel generalization of the Lloyd-Max algorithm to realize locally optimal SMDSQs. Both level-constrained and entropy-constrained cases are considered. For both cases, locally optimal solutions are realized by iterative execution...
This paper presents a learning-based method called image super-resolution (SR) for generating a high-resolution (HR) image from a single low-resolution (LR) image. Recent research investigated the image SR problem using sparse coding, which is based on good reconstruction of any image local patch by a sparse linear combination of atoms from an overcomplete dictionary. However, sparse-coding-based...
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