International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Wavelet Transform and Its Applications in Image Processing and Signal Analysis

Author(s) Dr. Ramesh Prasad Aharwal, Dr. Sharda Pradhan
Country India
Abstract A Wavelet Transform (WT) is a mathematical technique that transforms a signal into different frequency components, each analyzed with a resolution that matches its scale. Wavelets are small waves with limited duration and they possess both time and frequency localization, which means they can capture both high-frequency and low-frequency information simultaneously. There are several types of wavelet transforms, and, depending on the application, one may be preferred to the others. For a continuous input signal, the time and scale parameters can be continuous leading to the Continuous Wavelet Transform (CWT) and Discrete wavelets. Image processing is a critical area in modern computing with applications ranging from medical imaging to remote sensing and computer vision. Traditional Fourier analysis has limitations in capturing localized features in images due to its global nature. Wavelet Transform (WT), with its multi-resolution and localized time-frequency representation, provides a powerful alternative for analysing and processing visual information. This paper presents a comprehensive overview of the theory of wavelet transforms, their mathematical foundations, and applications in image processing and signal processing, including compression of images, denoising and feature extraction from images.
Keywords Wavelet Transform, Image Processing, Signal Analysis, DWT
Field Physical Science
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-03-15
DOI https://doi.org/10.36948/ijfmr.2026.v08i02.71472
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E-ISSN 2582-2160
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