Contourlet transform has been proved superior to wavelet in representation piecewise texture and contour characters in digital images. In order to improve the retrieval rate further, we studied the representation abilities of some different filters for texture features in two contourlet retrieval systems. The two systems both used Canberra distance for similarity measure, but different feature ...

The evaluation of retinal images is widely used to help doctors diagnose many diseases, such as diabetes or hypertension. Due to the acquisition process, retinal images often have low grey level contrast and dynamic range. This problem may seriously affect the diagnostic procedure and its results. Here we present a new multi-scale method for retinal image contrast enhancement based on the Conto...

A complete texture image retrieval system includes two techniques: texture feature extraction and similarity measurement. Specifically, similarity measurement is a key problem for texture image retrieval study. In this paper, we present an effective similarity measurement formula. The MIT vision texture database, the Brodatz texture database, and the Outex texture database were used to verify t...

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respecti...

This paper presents a new approach of texture image classification based on nonsubsampled contourlet transform, Local binary patterns and Support vector machines. Nonsubsampled contourlet transform and Local binary patterns are used to extract texture features of images, Support vector machines are used to classify texture images. Nonsubsampled contourlet transform has translation invariability...

In this paper we present a lossy image coder based in multiscale and directional contourlet transform which allows edge preserving in decompressed images. The preserving task is made by capture the edge points of an image using a robust and efficient edge detector known as Smallest Univalue Segment Assimilating Nucleus (SUSAN). The resulting edges coordinates are used as a priori knowledge of t...

The image retrieval problem has recently become more important and necessary because of the rapid growth of multimedia databases and digital libraries. Different search engines use different features to retrieve images from the database. In this paper, the Contourlet Transform is developed to retrieve similar images from the image database. By combining the Laplacian pyramid and the Directional...

Introduction: One of the major problems in the development of nuclear medicine images is the presence of noise. The noise level in nuclear medicine images is usually reduced by the analysis of imaging data in a Fourier transform environment. The main drawback of this environment belongs to low signal to noise ratio in high frequencies because removing noise frequencies may remove data and times...

In this paper, a multimodal image fusion algorithm based on multiresolution transform and particle swarm optimization (PSO) is proposed. Firstly, the source images are decomposed into low-frequency coefficients and high-frequency coefficients by the dual-tree complex wavelet transform (DTCWT). Then, the high-frequency coefficients are fused by the maximum selection fusion rule. The low-frequenc...