In digital photography, the consumer- and prosumer-level cameras produce images with an easily noticeable noise component, which is especially strong in images taken at high ISO rates. Scanned photos contain a similar film grain component. The noise and grain reduce the visual quality of digital images and resulting printouts. Neat Image is a digital filter specifically designed to reduce visible noise in digital photographic images produced by modern digital cameras, as well as film and flatbed scanners. Neat Image noise reduction algorithms are developed specifically for digital photography applications by a highly-qualified professional image processing research group. These algorithms surpass the quality of all classic noise reduction methods and even that of the wavelet-based methods. Although the wavelet-based methods were developed only 15-20 years ago and are still considered relatively modern, Neat Image uses an even newer and more efficient approach to noise reduction. This approach enables drawing a more clear distinction between noise and details in noisy images. This helps Neat Image reduce more noise and better preserve true details in digital photos and scans. A device noise profile is a reusable analysis of noise properties of an image acquisition device (a digital camera, scanner, etc.) working in a certain mode. Using a noise profile for an imaging device in effect makes Neat Image noise reduction custom-tailored to this imaging device.
Device noise profile is a novel concept originally introduced by Neat Image team and supported by Neat Image user community who create noise profiles for many digital cameras and scanners. Auto Profile provides the easiest and quickest way to automatically build a noise profile in just one click
Auto Profile finds one primary analysis area (shown in GUI) and multiple secondary areas to build an accurate profile. Pro edition: full support for 8-, 16-bit and 32-bit images, unlimited batching. This edition is intended for professionals who process large amounts of images and work with high-bitdepth images.
Comments