Image Denoising

Image Denoising refers to restoring a clean image by removing undesirable noise distortions from input image. Image denoising is a classic image processing and computer vision problem and has been studied for decades while still is challenging. Numerous image denoiser have been provided from classic algorithms with mathematical principle to recent methods based on machine learning and deep learning advances. Using saiwa interface you may try both approaches: a classic method which is called “Non-blind DCT-based method” and a deep learning method which is called “multi-stage learning”. For technical details of both algorithms please refer to the corresponding white paper. To request demos of other denoising algorithms, you can simply fill the Request for Customization form or leave us a ticket. saiwa image Denoising service has the following advantages:  

• Providing both classic and deep learning denoisers: fast low-complex non-blind denoiser and parameter-less blind deep learning denoiser
• Less halo artifacts
• Parameter adjustment to try classic method on images with different noise standard deviations
• Image aggregation to apply the algorithm on several images at once
• Preview and download the resulting images
• Exporting and archiving the results in user cloud space or locally
• Service customization by saiwa© team using “Request for customization” optionImages Denoising may apply as a pre-processing step in any image processing application that works with input noisy images. To mention only a few:1. Medical image processing 2. Industrial machine vision application 3. Astronomical imaging 4. Pre-processing stage of machine vision systems

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