Wavelet transforms enable us to represent signals with a high degree of scarcity. Wavelet thresholding is a signal estimation technique that exploits the capabilities of wavelet transform for signal denoising. The aim of this project was to study various thresholding techniques such as SureShrink, VisuShrink and BayeShrink and determine the best one for image denoising.

Lossy pulse-echo ultrasonic image compression by a JPEG baseline system is permitted by DICOM. In addition to the use of JPEG, use of JPEG2000 will be approved in the near future. The main features of JPEG2000 are use of wavelet transform and ROI (Region of Interest) method. It is expected that wavelet transform is more effective than Fourier transform for ultrasonic echo signal / image process...

Image compression plays a vital role in digital image processing. The need for image compression becomes apparent when number of bits per image are computed resulting from typical sampling rates and. quantization methods. For example, the amount of storage required for given images is (i) a low resolution, TV quality, color video image which has 512 x 512 pixels/color,8 bits/pixel, and 3 colors...

This paper presents a novel image denoising technique by using Principal Component Analysis (PCA) and Wavelet transform. The noisy image can be decomposed by the PCA into different blocks. Eigen values for each block is calculated and the common vector from each block is eliminated. The noise under consideration is AWGN and is treated as a Gaussian random variable. The denoised image obtained b...

The application of the wavelet transform in image processing is most frequently based on a separable construction. While simple, such an approach is not capable of capturing properly all 2D properties in images. In this paper, a new truly separable multidirectional transform is proposed with a subsampling method based on lattice theory. Applications are possible in many areas of image processin...

A new image sharing method, based on the reversible integer-to-integer (ITI) wavelet transform and Shamir’s (r,m) threshold scheme is presented, that provides highly compact shadows for real-time progressive transmission. This method, working in the wavelet domain, processes the transform coefficients in each subband, divides each of the resulting combination coefficients into m shadows, and al...

Copyright protection has become a need in today’s world. To achieve a secure copyright protection we embedded some information in images and videos and that image or video is called copyright protected. The embedded information can’t be detected by human eye but some attacks and operations can tamper that information to breach protection. So in order to find a secure technique of copyright prot...

Clustering techniques are mostly unsupervised methods that can be used to organize data into groups based on similarities among the individual data items. Most clustering algorithms do not rely on assumptions common to conventional statistical methods, such as the underlying statistical distribution of data, and therefore they are useful in situations where little prior knowledge exists. The po...

This paper deals with processing of wireless capsule endoscopy (WCE) images from gastrointestinal tract, by extracting textural features and developing a suitable classifier to recognize as a normal or abnormal /tumor image. Images obtained from WCE are prone to noise. To reduce the noise, filtration technique is used. The quality of the filtered image is degraded, so to enhance the quality of ...

We compress the document image by the use of LZMA algorithm. It is stands for Lempel-Ziv-Markov chain algorithm. It is used for lossless compression. In pre-processing we remove the noise from the image. Then we apply the wavelet transform to the image. It will decompose the image. Here we quantize the image by the use of wavelet. It is more robust under transmission. For encoding process it wi...