The process of partitioning an image into some different meaningful regions with the homogeneous characteristics is called the image segmentation which is a crucial task in image analysis. This study presents an efficient scheme for unsupervised colour–texture image segmentation using neutrosophic set (NS) and nonsubsampled contourlet transform (NSCT). First, the image colour and texture inform...

We describe a method for removing acoustic-optical image noise, based on a statistical model of the decomposed contourlet coefficients. This method proposes an alpha-stable multivariate shrinkage (MS) probability density function to model neighborhood contourlet coefficients. Then, according to the proposed PDF model, we design a maximum a posteriori (MAP) estimator, which relies on a Bayesian ...

In this paper, we propose to improve image decomposition algorithms in the case of noisy images. In [1, 9], the authors propose to separate structures, textures and noise from an image. Unfortunately, the use of separable wavelets shows some artefacts. In this paper, we propose to replace the wavelet transform by the contourlet transform which better approximate geometry in images. For that, we...

Evidently, the results of a face recognition system can be influenced by image illumination conditions. Regarding this, the authors proposed a system using wavelet-based contourlet transform normalization as an efficient method to enhance the lighting conditions of a face image. Particularly, this method can sharpen a face image and enhance its contrast simultaneously in the frequency domain to...

In this work, we study and analyze the contourlet transform for low bit-rate image coding. This image-based geometrical transform has been recently introduced to efficiently represent images with a spars set of coefficients. In order to explore the potentiality of this new transform as a tool for image coding, we developed a direct coding scheme that is based on using non-linear approximation o...

Image fusion is the process of combining relevant information from two or more images into a single fused image. The resulting image will be more informative than any of the input images. The fusion in medical images is necessary for efficient diseases diagnosis from multimodality, multidimensional and multi parameter type of images. This paper describes a multimodality medical image fusion sys...

Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. In general, the majority of registration methods consist of the following four steps: feature extraction, feature matching, transform modeling, and finally image resampling. As the accuracy of a registration process is highly dependent to the fe...