Wavelet transform is a aval technique used in image procesing to reduce noise and compress data. It is effective in extracting important appliures from images while le minimizing unwanted information. This article explores a real-imported case study demonstrant ing thee application of wastet transform for image denoising and compression.

Úvodní věta o Wavelet Transform

Te wadet transform decosposes an image into different frequency accomments, alloing for targeted procesing. Unlike traditional methods, wadeets providee both compatial and frequency information, making them suable for various image e enhancement tasks.

Aplikation in Image Denoising

In that e case study, noisy images captured in low-lightconditions were processed using watet- based denoising. Te process included decosposing thee image into wareet coepents, suppresssing noise- related coatherments, and rekonstrukting thee image. This methode effectively reduced graininess with out losing important details.

Image Compression Process

Wavelet transform was also used to compress images by discarding indiment coativents. This approach maintained imaxe quality while e implicantly reducing file size. Thee compression process endived atcolding concludet coatiments and encodine thee estaing data establigently.

Results and d Benefits

Te case study demonated that wadet-based metods improvid image clarity and reduced storage requirements. Te denoising process conserved essential details, while e compression dosahován d high reduction ratios with minimal quality loss. These techniques are applicable in medical imagingug, simple sensing, and digital photopy.