SAR-BM3D is one of the state of the art despeckling algorithms for SAR images. However, when tackling with high resolution SAR images, it often has an unsatisfying despeckling performance in the homogeneous smooth regions, together with a high time complexity. In this paper, a novel downsampled SAR-BM3D despeckling approach combined with edge compensation is proposed. The proposed algorithm con...

We propose a novel approach for generating high quality visible-like images from Synthetic Aperture Radar (SAR) images using Deep Convolutional Generative Adversarial Network (GAN) architectures. The proposed approach is based on a cascaded network of convolutional neural nets (CNNs) for despeckling and image colorization. The cascaded structure results in faster convergence during training and...

This paper presents despeckling and information extraction using non-quadratic regularization. The novelty of this paper is that instead of the Gaussian prior model a Gauss-Markov random field model is chosen, because it can efficiently model textures in the images. The iterative procedure consist of noise-free image and texture parameter. The experimental results show that the proposed method ...

Remote sensing (RS) from airborne and spaceborne carriers has found numerous applications [24]. Radar RS is applied alongside with other types of imaging sys tems and it provides certain benefits compared to oth er RS systems as ability to work during day and night and possibility to operate in bad weather conditions [15]. However, acquired radar images formed by mod ern synthetic aperture rada...

Speckle is a random multiplicative noise which obscures the perception and extraction of fine details in ultrasound image and despeckling is necessary to improve the visual quality for better diagnoses. Preliminary treatment of images before segmentation and classification includes despeckling as one of the important steps. This paper aims at introducing the possible range of image speckle corr...

In this paper, we present a novel approach for joint decorrelation and despeckling of synthetic aperture radar (SAR) imagery. An iterative maximum a posterior estimation is performed to obtain the correlation and speckle-free SAR data, which incorporates a correlation model which realistically explores the physical correlated process of speckle noise on signal in SAR imaging. The correlation mo...

⎯A novel and efficient speckle noise reduction algorithm based on Bayesian contourlet shrinkage using contourlet transform is proposed. First, we show the sub-band decompositions of SAR images using contourlet transforms, which provides sparse representation at both spatial and directional resolutions. Then, a Bayesian contourlet shrinkage factor is applied to the decomposed data to estimate th...

The Stroke is one of the most important causes of death in the world and the leading cause of serious, long-term disability. There is an urgent need for better techniques to diagnose patients at risk of stroke based on the measurements of the intima media thickness (IMT) and the segmentation of the atherosclerotic carotid plaque. The objective of this work was to carry out a comparative evaluat...

In this paper, we propose a new method for synthetic aperture radar (SAR) image despeckling via L0-minimization strategy, which aims to smooth homogeneous areas while preserve significant structures in SAR images. We argue that the gradients of the despeckled images are sparse and can be pursued by L0-norm minimization. We then formularize the despeckling of SAR images as a global L0 optimizati...

Speckle is a random multiplicative noise which obscures the perception and extraction of fine details in ultrasound image and despeckling is necessary for better diagnosis. The main aim of despeckling is to keep the important features such as edges of the ultrasound image. In this paper an adaptive window hybrid median filter is proposed for despeckling of medical ultrasound images. In the prop...