IMAGE PROCESSING APPARATUS AND METHOD THEREFOR

• US 20120148108A1
• Filed: 12/06/2011
• Published: 06/14/2012
• Est. Priority Date: 12/13/2010
• Status: Abandoned Application

• Current Assignee: Canon Ayutthaya Limited (Canon Inc.)
• Original Assignee: Canon Ayutthaya Limited (Canon Inc.)
• Inventors: YAHATA, KAZUHIRO
• Application Number:
  US13/312,117
• Publication Number:
  US 20120148108A1
• Time in Patent Office: Days
• US Class Current: 382/106
• CPC Class Codes: G01S 11/12 using electromagnetic waves other than radio waves
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/20048 Transform domain processing
• CPC Class Codes: G06T 2207/20056 Discrete and fast Fourier transform, [DFT, FFT]
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 7/50 Depth or shape recovery

Abstract

Image capturing data captured by using an imaging optical system including an iris with an aperture having no point symmetry is input. An imaging parameter for the imaging optical system when the image capturing data is captured is captured. A spectrum of the input image capturing data is calculated. Optical characteristic information corresponding to an imaging parameter and an object distance and a spectrum model are obtained. A predictive model is generated as a spectrum model corresponding to the input image capturing data by using the imaging parameter, optical characteristic information, and spectrum model. An evaluation function is generated by using the spectrum of the image capturing data and the predictive model. The actual distance of the object included in an image represented by the image capturing data is estimated by using the evaluation function and a statistical method.

Claims

1. An image processing apparatus comprising:

an inputting section, configured to input image capturing data captured by using an imaging optical system including an iris with an aperture having no point symmetry;

an obtaining section, configured to obtain an imaging parameter for the imaging optical system when the image capturing data is captured;

a calculator, configured to calculate a spectrum of the input image capturing data;

a storing section, configured to store optical characteristic information of the imaging optical system and a spectrum model of image capturing data;

a model generator, configured to generate a predictive model as a spectrum model corresponding to the input image capturing data by using the imaging parameter, optical characteristic information corresponding to the imaging parameter and an object distance, and the spectrum model;

a function generator, configured to generate an evaluation function by using the spectrum of the image capturing data and the predictive model; and

an estimator, configured to estimate an actual distance of the object included in an image represented by the image capturing data by using the evaluation function and a statistical method.

2. The apparatus according to claim 1, wherein the estimator comprises:

an extractor, configured to extract an evaluation function whose value is minimum at positions corresponding to distances shorter and longer than the object distance represented by the imaging parameter; and

a determiner, configured to determine, as a plurality of distance candidates corresponding to actual distances of the object included in the image, object distances obtained when a predictive model used for generation of the extracted evaluation function is generated.

3. The apparatus according to claim 2, wherein the estimator further comprises:

a restoring section, configured to restore a blur of a spectrum of the image capturing data by using optical characteristic information corresponding to each of the plurality of distance candidates; and

a computation section, configured to calculate an autocorrelation of a phase of a spectrum of image capturing data after the restoration.

4. The apparatus according to claim 3, wherein the estimator determines one of the plurality of distance candidates as an estimated value of an actual distance of the object by using an autocorrelation calculated for each of the plurality of distance candidates.

5. The apparatus according to claim 1, wherein the storing section further stores a noise characteristic of image capturing data, and the model generator adds noise represented by a noise characteristic corresponding to the imaging parameter to the predictive model.

6. An image processing method comprising using a processor to perform the steps of:

inputting image capturing data captured by using an imaging optical system including an iris with an aperture having no point symmetry;

obtaining an imaging parameter for the imaging optical system when the image capturing data is captured;

calculating a spectrum of the input image capturing data;

storing optical characteristic information of the imaging optical system and a spectrum model of image capturing data;

generating a predictive model as a spectrum model corresponding to the input image capturing data by using the imaging parameter, optical characteristic information corresponding to the imaging parameter and an object distance, and the spectrum model;

generating an evaluation function by using the spectrum of the image capturing data and the predictive model; and

estimating an actual distance of the object included in an image represented by the image capturing data by using the evaluation function and a statistical method.

7. A non-transitory computer readable medium storing a computer-executable program for causing a computer to perform an image processing method comprising the steps of:

inputting image capturing data captured by using an imaging optical system including an iris with an aperture having no point symmetry;

obtaining an imaging parameter for the imaging optical system when the image capturing data is captured;

calculating a spectrum of the input image capturing data;

storing optical characteristic information of the imaging optical system and a spectrum model of image capturing data;

generating a predictive model as a spectrum model corresponding to the input image capturing data by using the imaging parameter, optical characteristic information corresponding to the imaging parameter and an object distance, and the spectrum model;

generating an evaluation function by using the spectrum of the image capturing data and the predictive model; and

estimating an actual distance of the object included in an image represented by the image capturing data by using the evaluation function and a statistical method.