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  2. Video denoising - Wikipedia

    en.wikipedia.org/wiki/Video_denoising

    Video denoising is the process of removing noise from a video signal. Video denoising methods can be divided into: Video denoising methods can be divided into: Spatial video denoising methods, where image noise reduction is applied to each frame individually.

  3. Noise reduction - Wikipedia

    en.wikipedia.org/wiki/Noise_reduction

    Noise reduction is the process of removing noise from a signal. Noise reduction techniques exist for audio and images. Noise reduction algorithms may distort the signal to some degree. Noise rejection is the ability of a circuit to isolate an undesired signal component from the desired signal component, as with common-mode rejection ratio.

  4. Median filter - Wikipedia

    en.wikipedia.org/wiki/Median_filter

    The median filter is a non-linear digital filtering technique, often used to remove noise from an image, [1] signal, [2] and video. [3] Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image).

  5. Krisp - Wikipedia

    en.wikipedia.org/wiki/Krisp

    Krisp's main product is a software application that can remove background noises and voices from audio in real-time. The software uses machine learning algorithms to analyze the audio signal and separate the speech from background noise, allowing the speech to be output in clear, noise-free audio. This technology has a wide range of ...

  6. Comparison of video converters - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_video_converters

    They may recompress the video to another format in a process called transcoding, or may simply change the container format without changing the video format. The disadvantages of transcoding are that there is quality loss when transcoding between lossy compression formats, and that the process is highly CPU -intensive.

  7. Digital image processing - Wikipedia

    en.wikipedia.org/wiki/Digital_image_processing

    Noise and Distortions: Imperfections in images due to poor lighting, limited sensors, and file compression can result in unclear images that impact accurate image conversion. Variability in Image Quality : Variations in image quality and resolution, including blurry images and incomplete details, can hinder uniform processing across a database.

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