Image noise reduction device and method

Abstract

A spatial noise reduction unit (20) calculates a spatial NR pixel value (Snr) which is obtained by reducing spatial noise from an input pixel value (Pin). A temporal noise reduction unit (30) calculates a temporal NR pixel value (Tnr) which is obtained by reducing temporal noise from the input pixel value (Pin). A temporal noise reduction result determination unit (50) compares the magnitudes of the input pixel value (Pin) and the spatial NR pixel value (Snr) and the magnitude of the temporal NR pixel value (Tnr), and on the basis of the result of the comparison, outputs any of the pixel values as the result of the noise reduction (output pixel value (Pout)). Consequently, the temporal noise reduction can be strongly applied to a moving image while suppressing occurrences of after images in a moving image region.

Description

technical field [0001] The present invention relates to an image noise removal device and method, in particular to an image noise removal device and method capable of easily and effectively removing noise contained in moving images. Background technique [0002] A moving image captured by an imaging device such as a digital video camera or a digital still camera includes noise due to the imaging environment and the characteristics of the image sensor. These noises include optical shot noise, dark noise, fixed pattern noise, and circuit noise. Since these noises cause image quality (image quality) to decrease, it is necessary to perform noise reduction (Noise Reduction, NR) processing, that is, to remove (or reduce) noise contained in moving images. [0003] As a noise removal method, there is known a method of smoothing the pixel value of the target pixel by using the pixel values ​​of neighboring pixels located in the vicinity of the target pixel to be processed. In order...

AI Technical Summary

Problems solved by technology

However, if the smoothing process is strengthened in the time direction of the moving image, afterimages will be generated around the moving image area and the image quality will be degraded.

In this way, there is a trade-off relationship between suppressing afterimages in the moving image field and enhancing smoothing processing in the time direction of moving images. Therefore, there is still a technical problem that the temporal noise removal effect cannot be sufficiently improved for moving images.

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