**6. References**

446 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology

a) Lena b) Elaine

Fig. 13. Reconstructed a) 'Lena' and b) 'Elaine' test images at compression ratio of 40 using

I) MSB

II) JPEG

III) JPEG 2000

I) MSB codec, II) JPEG and III) JPEG2000.


**19** 

*India* 

**Image Denoising Based on** 

*Department of Computer Science, Avinashilingam University for Women,* 

*Coimbatore, Tamil Nadu,* 

**Wavelet Analysis for Satellite Imagery\***

Digital images are prone to a variety of types of noise. Noise is the result of errors in the image acquisition process that result in pixel values that do not reflect the true intensities of the real scene (Gagnon & Smaili, 1996). There are several ways that noise can be introduced into an image, depending on how the image is created. For example if the image is scanned from a photograph made on film, the film grain is a source of noise. Noise can also be the result of damage to the film, or be introduced by the scanner itself. If the image is acquired directly in a digital format, the mechanism for gathering the data (such as a CCD detector) can introduce noise. Electronic transmission of image data can introduce noise. Noise is considered to be any measurement that is not part of the phenomena of interest. Noise can be categorized as Image data independent noise and

Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution matched to its scale (Durand & Froment,1992). They have advantages over traditional Fourier methods in analyzing physical situations where the signal contains discontinuities and sharp spikes. Wavelets were developed independently in the fields of mathematics, quantum physics, electrical engineering, and seismic geology. Interchanges between these fields during the last ten years have led to many new wavelet applications such as image compression, turbulence,

Synthetic aperture radar is a radar technology that is used from satellite or airplane (Lee,Jukervish 1994). It produces high resolution images of earth's surface by using special signal processing techniques. Synthetic aperture radar has important role in gathering information about earth's surface because it can operate under all kinds of weather condition (whether it is cloudy, hazy or dark).However acquisition of SAR images face

 Copyright notice : This proposal and its intellectual property right belongs to the author and has been submitted for publication as a chapter in the book entitled *"Wavelet Transform"* to be published by the INTECH**,** Open Access Publisher, Croatia. As a courtesy to the publisher, this proposal may not be

**1. Introduction** 

image data dependent noise.

 \*

human vision, radar, and earthquake prediction.

reproduced or distributed in any form.

Parthasarathy Subashini and Marimuthu Krishnaveni

