Differences of digital camera resolution metrology to describe noise reduction artifacts

Noise reduction in the image processing pipeline of digital cameras has a huge impact on image quality. It may result in loss of low contrast fine details, also referred to as texture blur. Previous papers have shown, that the objective measurement of the statistical parameter kurtosis in a reproduction of white Gaussian noise with the camera under test correlates well with the subjective perception of these ramifications. To get a more detailed description of the influence of noise reduction on the image, we compare the results of different approaches to measure the spatial frequency response (SFR). Each of these methods uses a different test target, therefore we get different results in the presence of adaptive filtering. We present a study on the possibility to derive a detailed description of the influence of noise reduction on the different spatial frequency sub bands based on the differences of the measured SFR using several approaches. Variations in the underlying methods have a direct influence on the derived measurements, therefore we additionally checked for the differences of all used methods.