Signal processing apparatus and signal processing method

Patent metadata

Field	Value
Publication number	US-2017287125-A1
Application number	US-201715458386-A
Country	US
Kind code	A1
Filing date	Mar 14, 2017
Priority date	Mar 31, 2016
Publication date	Oct 5, 2017
Grant date	—

Abstract

A signal processing apparatus includes an acquisition unit that acquires input data and detection target data, a noise strength setting unit that sets a noise strength K used to a predetermined stochastic resonance processing and a stochastic resonance processing unit that performs the predetermined stochastic resonance processing and outputs processed data. The predetermined stochastic resonance processing is a processing based on a formula in which processed data J(x) is represented by I(x), the noise strength K and the threshold value T and the processed data J(x) corresponds to a result in a case where M is infinite in the following formula,

J
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M

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j
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(

x
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m

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.

The noise strength setting unit sets the noise strength based on a function of a correlation coefficient between the result of the predetermined stochastic resonance processing and the detection target data and the noise strength K.

First claim

What is claimed is:

1 . A signal processing apparatus, comprising:
an acquisition unit configured to acquire input data having a plurality of input signals I(x) corresponding to a plurality of pixel position X respectively, and detection target data having detection target signals as a target to be detected; a noise strength setting unit configured to set, based on the input data and the detection target data, a noise strength K used to subject the input signals I(x) to a predetermined stochastic resonance processing, the noise strength K showing the strength of noise added to the input signals I(x); and a stochastic resonance processing unit configured to use the noise strength K set by the noise strength setting unit and a threshold value T to quantize the input signals to subject the input signals I(x) to the predetermined stochastic resonance processing to output processed data, wherein: the predetermined stochastic resonance processing is a processing based on a formula in which processed data J(x) is represented by I(x), the noise strength K and the threshold value T and the processed data J(x) corresponds to a result in a case where M is infinite in the following formula,

J
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(
x
)

=

1
M

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∑

m
=
1

M

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j
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(

x
,
m

)

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:

j(x,m) being a result of a processing in which a value obtained by multiplying a random number noise N(x,m) of 1 to 0 by the noise strength K is added to the input signal I(x,m) and further binarized, M indicating the number of the processing among which the random number noises are different and m indicating one of the plurality processing the noise strength setting unit sets the noise strength K based on a function of a correlation coefficient and the noise strength K:
the correlation coefficient showing a correlation between the result of a case where each of the plurality of input signals I(x) is subjected to the predetermined stochastic resonance processing and the detection target data.

2 . The signal processing apparatus according to claim 1 , wherein
the noise strength setting unit sets the noise strength K in a case where the correlation coefficient becomes a local maximum value in the function as a noise strength K used to perform the predetermined stochastic resonance processing.

3 . The signal processing apparatus according to claim 1 , wherein
the noise strength setting unit sets the noise strength K so that a value shown by the correlation coefficient of the input data and the detection target data in a case where the predetermined stochastic resonance processing is performed is larger than a value shown by the correlation coefficient in a case where the predetermined stochastic resonance processing is not performed.

4 . The signal processing apparatus according to claim 1 , wherein
the noise strength setting unit sets the noise strength K within a range higher than the noise strength in a case where the correlation coefficient becomes a local maximum value and lower than the noise strength in a case where the correlation coefficient becomes convergent at a fixed value.

5 . The signal processing apparatus according to claim 1 , wherein
the noise is white noise having the noise strength K set by the noise strength setting unit as an upper limit.

6 . The signal processing apparatus according to claim 1 , wherein
the noise is normal distribution noise having an upper limit at the noise strength K set by the noise strength setting unit.

7 . The signal processing apparatus according to claim 1 , further comprising:
a threshold value setting unit configured to set the threshold value T for the binary processing used in the predetermined stochastic resonance processing for the input signals I(x), based on the input data and the detection target data.

8 . The signal processing apparatus according to claim 1 , wherein
the detection target data is prepared as a plurality of pieces of detection target data having different phases with respect to the pixel position; the acquisition unit acquires the plurality of pieces of the detection target data; the noise strength setting unit sets the noise strength K for each of the plurality of pieces of the detection target data; and the stochastic resonance processing unit uses the respective noise strengths set by the noise strength setting unit to subject the input signals I(x) to the predetermined stochastic resonance processing; and the signal processing apparatus further comprises a selection unit configured to compare a plurality of results of the predetermined stochastic resonance processing executed by the stochastic resonance processing unit to select one result.

9 . The signal processing apparatus according to claim 1 , wherein
the predetermined stochastic resonance processing is performed by using the following formula to calculate the processed data J(x) obtained from the input data I(x).

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Assignees

• Canon Kk

Inventors

• Tanaka Wakako
• Hori Shinjiro
• Suwa Tetsuya
• Ishikawa Tomokazu

Classifications

• H04N1/504

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• G06T2207/30176

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• H04N1/409 Primary

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• G06T2207/10004

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