Image Compression using Wavelet Transform

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Original Image Compressed Image

PSNR:

Introduction

This web application offers a platform to perform image compression using the Discrete Wavelet Transform (DWT) technique.

The user can select an image and choose from various wavelet types for compression. The application allows adjusting the number of levels and bits for the compression process.

The compressed image and its quality, measured by the Peak Signal-to-Noise Ratio (PSNR), are displayed on the same page.

This tool aims to make it easier to understand the trade-offs between different compression parameters and image quality.

Wavelet Transform

The Discrete Wavelet Transform (DWT) is a powerful tool for signal and image processing. It decomposes a signal into different frequency components, allowing for efficient compression and analysis.

By applying the DWT to an image, we can separate the image into different frequency bands, which can be compressed independently. This process helps in reducing the size of the image while preserving important details.

Compression Parameters

The key parameters for image compression using the DWT are:

Peak Signal-to-Noise Ratio (PSNR)

The PSNR is a metric used to measure the quality of the compressed image compared to the original image. It provides a quantitative measure of the distortion introduced during compression, with higher values indicating better quality.

The PSNR is calculated as:

PSNR = 10 * log10(MAX2 / MSE)

Where:

Applications

Image compression using the DWT is widely used in various applications, including:

Images courtesy of Radiopaedia.org.