In this paper we present a Block Matching approach to registration of medical 2D images IRM/IRM. The registered images are assumed to be rigidly aligned before starting this procedure. The sum of absolute differences (SAD), sum of squared differences (SSD), mutual information (MI) and correlation coefficient (CC) are used as measures of similarity to determine the similarity between images as w...

In video coding standards, such as MPEG-4 and H.263, one important question is how to determine motion vectors for motion compensation in the INTER mode. Usually the sum of absolute differences (SAD) or the sum of squared differences (SSD) is employed as a matching criterion. Although these criteria are related to the distortion, they do not consider the bit rate appropriately. If we want to co...

Many visual matching algorithms can be described in terms of the features and the inter-feature distance or metric. The most commonly used metric is the sum of squared differences (SSD), which is valid from a maximum likelihood perspective when the real noise distribution is Gaussian. However, we have found experimentally that the Gaussian noise distribution assumption is often invalid. This im...

We present a new block matching criterion for motion estimation in video coding that will give better encoded video quality than the commonly used sum of absolute differences (SAD) or even sum of squared differences (SSD) criteria. The new criterion tends to concentrate the discrete cosine transformed block energy into DC frequency which may allow coding the AC coefficients with less bits. The ...

Many visual matching algorithms can be described in terms of the features and the inter-feature distance or metric. The most commonly used metric is the sum of squared differences (SSD), which is valid from a maximum likelihood perspective when the real noise distribution is Gaussian. However, we have found experimentally that the Gaussian noise distribution assumption is often invalid. This im...

In this paper we present a hardware architecture for the Sum of Absolute Difference (SAD) technique. This paper also gives the design details and the implementation results for an FPGA based core that permits realisation of a high speed matching algorithm for real time image processing applications. The matching criterion chosen is the SAD algorithm The implementation provides the correct posit...

A simple linear averaging of the outputs of several networks as e.g. in bagging 3], seems to follow naturally from a bias/variance decomposition of the sum-squared error. The sum-squared error of the average model is a quadratic function of the weighting factors assigned to the networks in the ensemble 7], suggesting a quadratic programmingalgorithm for nding the \optimal"weighting factors. If ...

Image matching is an inarguably important operation for many practical sophisticated systems in machine vision and medical diagnosis. Many gray-level image matching applications use the sum-of-squared-difference (SSD) or sum-ofabsolute-differences (SAD), which are very sensitive to noise. Almost all images have some kind of noise, which causes the matching tasks significantly difficulty. In thi...