Image enhancement using Moving window-based double Haar wavelet transform

In the image processing scenario the image enhancement takes high importance .Among so many image enhancement techniques the image enhancement is one of the main way. Visual information transmitted in the form of digital images is becoming a major method of communication in the modern age, but the image obtained after transmission is often corrupted with noise. The received image needs processing before it can be used in applications. Image enhancement involves the manipulation of the image data to produce a visually high quality image. Different noise models including additive and multiplicative types are used. They include Gaussian noise, Salt and Pepper noise, Speckle noise and Brownian noise. But wavelet transform considered to be better when compared with traditional techniques like median filtering etc.The proposed Double Haar Wavelet transform can make the image enhancement more effectively because of its improved low pass filter. Here, we propose an improved way in the choice of moving windows which can realize protecting the details and smoothing the noise. The estimate error of the wavelet coefficient for a pixel does not influence the estimates of the other pixels in the image. This technique can be used in the weather forecasting applications, for cleaning satellite images, in photo studios and in internet applications, etc, where the images are affected by Gaussian noise.