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In this paper a framework for image quality assessment (IQA) is introduced based on the properties of receptive fields (RFs) which are the primary mechanism for detection of visual patterns in the human visual system (HVS). The proposed framework offers a probabilistic approach to the perceptual IQA, based on the probability of detecting discrepancies (distortion) between the corresponding features...
In this paper we introduce a statistical framework for image quality assessment based on the properties of hierarchical receptive fields (RFs) which are the primary mechanism for detection of visual patterns in the human visual system (HVS). We show how this frame work can be used to learn about different aspects of RFs such as the shape and size of RFs in the early vision and the directional preference...
In this paper a framework is proposed for efficient entropy coding of data which can be represented by a parametric distribution model. Based on the proposed framework, an entropy coder achieves coding efficiency by estimating the parameters of the statistical model (for the coded data), either via maximum a posteriori (MAP) or Maximum Likelihood (ML) parameter estimation techniques. The problem of...
In this paper a novel method to estimate the required bits for representing the coded (quantized) coefficients within a block of natural video sequences is proposed. The proposed method assumes a parameterized probabilistic model for coded data and utilizes a maximum likelihood parameter estimation technique to estimate the model's parameters. The proposed method achieves a robust estimation of the...
In this paper, we analyze the formation of blocking artifacts as a result of quantization of the discrete cosine transform (DCT) coefficients. These artifacts are known to be the dominant distortion of lossy block-based hybrid image and video coding schemes when operating at very low data rates. Our analysis is carried out based on the theory of edge detection and by means of a mathematical framework...
To overcome the computational complexity in making optimized rate-distortion coding decisions (due to the calculation of actual rate) we propose a rate estimation scheme based on the maximum likelihood parameter estimation (MLPE) method.
This paper presents a fast method to estimate the required bits to encode a block of video data. The proposed method uses forward adaptive quantization (which uses the current sample information, not available at the decoder, to scale the sample value before and after quantization) to estimate the actual rate-distortion cost. Rate estimation has many applications in the art of video coding, where...
Conventional block-based video coding with subpixel motion compensation, requires a large pool of memory for storing up-sampled reference frames. The size of this memory for many applications, especially for encoding high definition source materials is a major design consideration. In this paper, the concept of reciprocal block matching is introduced based on the relativity of motion, especially,...
In this paper a novel approach to perceptual video coding is presented for block-based video coders. This is done by replacing purely mathematical models for measuring the distortion in video quality, such as mean squared error (MSE) or mean absolute difference (MAD), with a distortion model that measures the perceived distortion by an average human observer. Additionally, to keep the computational...
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