IP Library Granted Patent US 10,762,606
Granted Patent B2
US 10,762,606 · App. 15/816,678 · Granted Sep 1, 2020

Image processing apparatus and method for generating high quality image

Inventors: Shunta Tate (Tokyo, JP); Masakazu Matsugu (Yokohama, JP); Yasuhiro Komori (Tokyo, JP); Yusuke Mitarai (Tokyo, JP)
Assignee: Canon Kabushiki Kaisha
G06T5/003G06T5/001G06T5/50G06T15/205G06T2207/10024G06T2207/10028G06T2207/10048G06T2207/20081G06T2207/20084G06T2207/20216
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Quick Facts
Patent No.
US 10,762,606
App. No.
15/816,678
Granted
Sep 1, 2020
Kind
B2
Abstract

An image processing apparatus includes: an acquisition unit configured to acquire a plurality of images each capturing an identical target and having a different attribute; a derivation unit configured to derive features from the plurality of images, using a first neural network; an integration unit configured to integrate the features derived from the plurality of images; and a generation unit configured to generate a higher quality image than the plurality of images from the feature integrated by the integration unit, using a second neural network.

Claims (20)

1. An image processing apparatus comprising:

one or more processors; and

a memory coupled to the one or more processors, the memory having stored thereon instructions which, when executed by the one or more processors, cause the image processing apparatus to:

acquire a plurality of images being obtained by capturing an identical target from different viewpoint positions by a plurality of image capturing devices;

derive features from each of the plurality of images using corresponding one of first neural networks each provided for respective one of the viewpoint positions of the images;

integrate the features derived from the plurality of images; and

generate a high quality image of which quality is higher than that of each of the plurality of images, from the integrated features, using a second neural network.

2. The image processing apparatus according to claim 1 , wherein integrating the features includes determining a connectivity relationship of individual neural networks on a basis of a geometric positional relationship between viewpoint positions of the plurality of images and a viewpoint position of the high quality image.

3. The image processing apparatus according to claim 1 , wherein the one or more processors cause the image processing apparatus to integrate the features by determining a connectivity relationship of individual neural networks on a basis of case images for learning.

4. The image processing apparatus according to claim 1 , wherein the one or more processors cause the image processing apparatus to integrate the features in a plurality of stages, and determines an order of integration of the features on a basis of proximity of the viewpoint positions of the images corresponding to the features.

5. An image processing method comprising:

acquiring a plurality of images being obtained by capturing an identical target from different viewpoint positions by a plurality of image capturing devices;

deriving features from each of the plurality of images using corresponding one of first neural networks each provided for respective one of the viewpoint positions of the images;

integrating the features derived from the plurality of images; and

generating a high quality image of which quality is higher than that of each of the plurality of images, from the integrated features, using a second neural network.

6. A non-transitory computer-readable storage medium storing a program causing a computer to execute a method of image processing, the method comprising:

acquiring a plurality of images being obtained by capturing an identical target from different viewpoint positions by a plurality of image capturing devices;

deriving features from each of the plurality of images using corresponding one of first neural networks each provided for respective one of the viewpoint positions of the images;

integrating the features derived from the plurality of images; and

generating a high quality image of which quality is higher than that of each of the plurality of images, from the integrated features, using a second neural network.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2018
From: TATE, SHUNTA; MATSUGU, MASAKAZU; KOMORI, YASUHIRO; MITARAI, YUSUKE
To: CANON KABUSHIKI KAISHA
Reel/Frame 045281/0422 →
Priority Claims (1)
JP 2016-228042 · Nov 24, 2016 · national
Continuity (1)
Related Publication 20180144447A1 · May 24, 2018