The rapid expansion of the Internet and the wide use of digital data have increased the need for both efficient image database creation and retrieval procedure. The challenge in image retrieval is to develop methods that can capture the important characteristics of an image, which makes it unique, and allow its accurate identification. The focus of this paper is on the image processing aspects ...

The most ubiquitous neuron in the cerebral cortex, the pyramidal cell, is characterized by markedly different dendritic structure among different cortical areas. The complex pyramidal cell phenotype in granular prefrontal cortex (gPFC) of higher primates endows specific biophysical properties and patterns of connectivity, which differ from those in other cortical regions. However, within the gP...

The seminal work of Horn and Schunck is the first variational method for optical flow estimation. It introduced a novel framework where the optical flow is computed as the solution of a minimization problem. From the assumption that pixel intensities do not change over time, the optical flow constraint equation is derived. This equation relates the optical flow with the derivatives of the image...

This paper presents a lossy image compression scheme that employs a generalized rank-ordered prediction filter for pyramidal image coding. The proposed prediction method renders significantly reduced variance of the quantizer input. Consequently, the quality of the decompressed image is much enhanced due to the greatly reduced quantization distortion. Both analytical and simulation results show...

 Image restoration is an essential preprocessing step for many image analysis applications. In any image restoration techniques, keeping structure of the image unchanged is very important. Such structure in an image often corresponds to the region discontinuities and edges. The techniques based on partial differential equations, such as the heat equations, are receiving considerable attention i...

In this paper we present three classifiers used in automatic forms class identification. A first category of classifier includes the k-Nearest Neighbours (kNN) and the Multi-Layer Perceptron (MLP) classifiers. A second category corresponds to a new structural classifier based on tree comparison. On one hand, a low level information based on a pyramidal decomposition of the document image is use...

Speckle noise affects all coherent imaging systems including medical ultrasound. In medical images, noise suppression is a particularly delicate and difficult task. A tradeoff between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image content. Even though wavelets have been extensively used for denoising speckle ...

We propose resolution progressive Three-Dimensional Set Partitioned Embedded bloCK (3D-SPECK), an embedded wavelet based algorithm for hyperspectral image compression. The proposed algorithm also supports random Region-Of-Interest (ROI) access. For a hyperspectral image sequence, integer wavelet transform is applied on all three dimensions. The transformed image sequence exhibits a hierarchical...

Image segmentation is an important task in image processing and computer vision which attract many researchers attention. There are a couple of information sets pixels in an image: statistical and structural information which refer to the feature value of pixel data and local correlation of pixel data, respectively. Markov random field (MRF) is a tool for modeling statistical and structural inf...