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  2. Wikipedia:How to improve image quality - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:How_to_improve...

    Images can often be improved – or even transformed – by using graphics software such as Photoshop or the free GIMP and Paint.NET applications. Many other programs also have photo-enhancing tools, including facilities for semi-automatic image enhancement, so that you need only click a button, or choose a thumbnail, to have a positive effect on image quality.

  3. Signal-to-noise ratio (imaging) - Wikipedia

    en.wikipedia.org/wiki/Signal-to-noise_ratio...

    Signal-to-noise ratio (SNR) is used in imaging to characterize image quality.The sensitivity of a (digital or film) imaging system is typically described in the terms of the signal level that yields a threshold level of SNR.

  4. Imageability - Wikipedia

    en.wikipedia.org/wiki/Imageability

    Images in ImageNet are labelled using concepts in WordNet. Concepts that are easily expressed verbally, like "early", are seen as less "imageable" than nouns referring to physical objects like "leaf". Training AI models to associate concepts with low imageability with specific images can lead to problematic bias in image recognition algorithms.

  5. AI slop - Wikipedia

    en.wikipedia.org/wiki/AI_slop

    "AI slop", often simply "slop", is a term for low-quality media, including writing and images, made using generative artificial intelligence technology. [4] [5] [1] Coined in the 2020s, the term has a derogatory connotation akin to "spam".

  6. Peak signal-to-noise ratio - Wikipedia

    en.wikipedia.org/wiki/Peak_signal-to-noise_ratio

    The processing quality of 12-bit images is considered high when the PSNR value is 60 dB or higher. [ 3 ] [ 4 ] For 16-bit data typical values for the PSNR are between 60 and 80 dB. [ 5 ] [ 6 ] Acceptable values for wireless transmission quality loss are considered to be about 20 dB to 25 dB.

  7. Image quality - Wikipedia

    en.wikipedia.org/wiki/Image_quality

    Image quality can be assessed using objective or subjective methods. In the objective method, image quality assessments are performed by different algorithms that analyze the distortions and degradations introduced in an image. Subjective image quality assessments are a method based on the way in which humans experience or perceive image quality.