Noise reduction has been a traditional problem in image processing. Recent wavelet thresholding based denoising methods proved promising, since they are capable of suppressing noise while maintaining the high frequency signal details. However, the local space-scale information of the image is not adaptively considered by standard wavelet thresholding methods. In this paper, a new type of thresh...

The speckle corrupted image is a traditional problem in both biomedical and in synthetic aperture processing applications, including synthetic aperture radar (SAR). In a SAR image, speckle manifests itself in the form of a random pixel-to-pixel variation with statistical properties similar to those of thermal noise. Due to its granular appearance in an image, speckle noise makes it very difficu...

Selection of appropriate size windows or subimages is the most important step for thresholding images with non-uniform lighting. In this paper, a novel criteria function developed to partition into different sub thresholding. After partitioning, each subimage segmented by Otsu’s approaches. The performance proposed method validated on benchmark test degree uneven Based qualitative and quantitat...

In this paper, a Growing TASOM (Time Adaptive Self-Organizing Map) network called “GTASOM” along with a peak finding process is proposed for automatic multilevel thresholding. The proposed GTASOM is tested for image segmentation. Experimental results demonstrate that the GTASOM is a reliable and accurate tool for image segmentation and its results outperform other thresholding methods.

Medical images are corrupted by noises during its transmission and acquisition process. Noise reduction has been a traditional problem in image and signal processing. Medical images generally contains minute information about heart, brain, nerves etc therefore wrong diagnosis might not rescue the patient from harmful effects. In this paper we proposed an approach for image denoising based on wa...