Segmentation of adjoining objects in a noisy image is a challenging task in image processing. Natural images often get corrupted by noise during acquisition and transmission. Segmentation of these noisy images does not provide desired results, hence de-noising is required. In this paper, we tried to address a very effective technique called adaptive wavelet thresholding for de-noising, followed...

In 1992 David Donoho has introduced the term de-noising. Despite its advantages, this method isn't used yet in communications. The goal of this paper is to adapt this method to the requirements of communications, especially for low SNR signals. Our contribution is a new threshold's value search method, that realizes the maximization of the signal to noise ratio at the output of the de-noising s...

in this paper, an efficient algorithm is proposed for detection of vertical root fractures (vrfs) in periapical (pa), and cone-beam computed tomography (cbct) radiographs of nonendodontically treated premolar teeth. pa and cbct images are divided into some sub-categories based on the fracture space between the two fragments as small, medium, and large for pas and large for cbcts. these graphics...

The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts. Noise severely limits the utility of the recorded ECG and thus need to be removed, for better clinical evaluation....

Noise affects images during transmission or processing. The quality of image is affected by noise so to retain the quality of image an operation is performed that is called de-noising. De-noising basically deals with the removal of noise from noise contaminated version of image. There are different method of image de-noising depend upon the noise that is present in the image. This paper present...

Solar cell is known as a sustainable and environment friendly source of energy in nature. It converts sunlight directly into electricity with zero emission and also without side-effects on the environment. But, solar cells have optical and mechanical defects which include the type of micro crack, the size of crack, and the noise from electrical or electromechanical interference during the image...

De-noising and extraction of the weak signature are crucial to fault prognostics in which case features are often very weak and masked by noise. The wavelet transform has been widely used in signal de-noising due to its extraordinary time-frequency representation capability. In this paper, the performance of wavelet decomposition-based de-noising and wavelet filter-based de-noising methods are ...

Magnetic resonance images acquired with high temporal resolution often exhibit large noise artifacts, which arise from physiological sources as well as from the acquisition hardware. These artifacts can be detrimental to the quality and interpretation of the time-course data in functional MRI studies. A class of wavelet-domain de-noising algorithms estimates the underlying, noise-free signal by...

In ultrasonic testing of welding flaws, the reliability and quality of tests are considerably affected by noise and spurious signals. Thus, signal de-noising and increasing of the signal-noise ratio (SNR) are a key to successful application of ultrasonic NDT and NDE. At present, there are many methods for signal de-noising, such as median filtering, non-linear filtering, adaptive filtering, cor...

CT image De-noising is an important research topic both in image processing and biomedical engineering. Independent component analysis (ICA) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. The curvelet transform as a multiscale transform has directional parameters occurs at all scale...