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  2. 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 ...

  3. Noise (video) - Wikipedia

    en.wikipedia.org/wiki/Noise_(video)

    Noise (video) Noise in a CRT television (top) and flat screen television (bottom) Noise, static or snow screen captured from a VHS tape. Noise, commonly known as static, white noise, static noise, or snow, in analog video and television, is a random dot pixel pattern of static displayed when no transmission signal is obtained by the antenna ...

  4. 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 .

  5. Personalize your background image, sounds, and toolbar ...

    help.aol.com/articles/personalize-your...

    1. Sign in to Desktop Gold. 2. Click the Settings button. 3. Click Personalization. 4. Click the Sounds tab. 5. Click Customize My Sounds. 6. Search for a sound or select a category from the "All" menu at the top-right.

  6. Image editing - Wikipedia

    en.wikipedia.org/wiki/Image_editing

    Image editors may feature a number of algorithms which can add or remove noise in an image. Some JPEG artifacts can be removed; dust and scratches can be removed and an image can be de-speckled. Noise reduction merely estimates the state of the scene without the noise and is not a substitute for obtaining a "cleaner" image.

  7. Median filter - Wikipedia

    en.wikipedia.org/wiki/Median_filter

    The median filter operates by considering a local window (also known as a kernel) around each pixel in the image. The steps for applying the median filter are as follows: Choose a window of a specific size (e.g., 3x3, 5x5) centered around the pixel to be filtered. For our example, let’s use a 3x3 window.

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