Image signal processor

Abstract

An image signal processing apparatus solves a problem of an increase in noise component contained in an image signal due to the gamma correction when a signal level is in a region where a slope of conversion characteristic is sharp, which problem has been detected in an image signal processing apparatus including gamma correction processing performed for achieving nonlinear conversion.The image signal is input to each of LPFs 40 and 42 which differ in transmission characteristic, and a selector 44 selects either one of outputs from the LPFs to send the selected output to the gamma correction circuit. The switching by the selector 44 is controlled by the filter control circuit 32 . In the filter control circuit 32 , a comparator 60 compares a signal level of an object pixel with a threshold value R. In the case where the signal level of the object pixel is in the region where the slope of conversion characteristic is sharp (less than R), the selector 44 is so controlled as to select the output from the LPF 42 which has a lower cutoff frequency and a larger noise component elimination effect as compared with the LPF 40.

Description

technical field [0001] The present invention relates to an image signal processing device that performs gradation correction of an image signal, and particularly relates to suppression of noise in gradation correction processing based on nonlinear characteristics. Background technique [0002] As one of the image qualities of an imaging device such as a digital camera, there is gradation, and a gradation correction circuit for correcting it is generally provided. The gradation correction circuit converts the signal level of the input image signal according to a predetermined conversion characteristic function, and outputs the converted image signal. For example, a gamma correction circuit is also a circuit for gradation correction. Figure 6 is a schematic curve showing the transformation characteristics. The transformation characteristic is generally nonlinear, and in the part of the transformation characteristic curve whose slope is greater than 1, the gray scale is elong...

AI Technical Summary

Problems solved by technology

[0004] in such as Image 6 At the image signal level at which the slope of the conversion characteristic shown is large, there is a problem that the noise components (random noise, horizontal pull noise) included in the image signal also become large.

Especially in low input image signal levels, because the ratio of noise components relative to the image signal is relatively large, in such as Image 6 As shown, when the slope of the conversion characteristic is large at low input image signal levels, picture quality degradation due to amplified noise components becomes significant

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