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Adobe Enhanced Speech is an online artificial intelligence software tool by Adobe that aims to significantly improve the quality of recorded speech that may be badly muffled, reverberated, full of artifacts, tinny, etc. and convert it to a studio-grade, professional level, regardless of the initial input's clarity. [1]
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.
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.
This version adds Loudness, Noise Gate and Spectral Delete effects and adds Side-by-side view of waveforms and spectrograms. 2.3 September 29, 2018 This version adds Punch-and-Roll recording and upgrades to Macros, Play-at-Speed, Toolbars. From 2.3.2 on, a mod-script-pipe for driving Audacity from Python (can be enabled in Preferences). [27] 2.2
G'MIC (GREYC's Magic for Image Computing) is a free and open-source framework for image processing. It defines a script language that allows the creation of complex macros. Originally usable only through a command line interface, it is currently mostly popular as a GIMP plugin, [2] and is also included in Krita.
Apply simple or advanced effects or filters, including amplification, normalization, limiting, panning, compression, expansion, flanging, reverb, audio noise reduction, and equalization to change the audio. Playback sound (often after being mixed) that can be sent to one or more outputs, such as speakers, additional processors, or a recording ...
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Anisotropic diffusion can be used to remove noise from digital images without blurring edges. With a constant diffusion coefficient, the anisotropic diffusion equations reduce to the heat equation which is equivalent to Gaussian blurring. This is ideal for removing noise but also indiscriminately blurs edges too.
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