Synthetic aperture radar (SAR) images are mainly denoised by multiplicative speckle noise, which is due to the consistent behavior of scattering phenomenon known as speckle noise. This paper presents the basic concept, role and importance of Discrete Wavelet Transform (DWT) in the field of despeckling SAR images and also offers a study of SAR image quality on applying DWT on the speckled image ...

Medical ultrasound images are widely used for diagnostic purposes. A major problem regarding these images is in their inherent corruption by speckle noise. The presence of speckle noise severely hampers the interpretation and analysis of medical ultrasound images. The objective of the paper is to propose a method for removal of noise in the medical ultrasound images. The image noise content is ...

this paper, a new probability density function (pdf) is proposed to model the statistics of wavelet coefficients, and a simple Kalman's filter is derived from the new pdf using Bayesian estimation theory. Specifically, we decompose the speckled image into wavelet subbands, we apply the Kalman's filter to the high subbands, and reconstruct a despeckled image from the modified detail coefficients...

Deep learning (DL) in remote sensing has nowadays become an effective operative tool: it is largely used applications, such as change detection, image restoration, segmentation, and classification. With reference to the synthetic aperture radar (SAR) domain, application of DL techniques not straightforward due nontrivial interpretation SAR images, especially caused by presence speckle. Several ...

Detecting objects in synthetic aperture radar (SAR) imagery has received much attention recent years since SAR can operate all-weather and day-and-night conditions. Due to the prosperity development of convolutional neural networks (CNNs), many previous methodologies have been proposed for object detection. In spite advance, existing detection still limitations boosting performance because inhe...

The paper presents a novel despeckling method, based on Daubechies complex wavelet transform, for medical ultrasound images. Daubechies complex wavelet transform is used due to its approximate shift invariance property and extra information in imaginary plane of complex wavelet domain when compared to real wavelet domain. A wavelet shrinkage factor has been derived to estimate the noise-free wa...