Super-resolution image reconstruction method using analysis sparse representation

A low-resolution image, sparse representation technology, applied in the field of super-resolution image reconstruction using analytical sparse representation, can solve the problem that analytical sparse representation has not been proposed by others

Active Publication Date: 2013-04-17
CHINACCS INFORMATION IND
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So far, analytically sparse representations have not been prop

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  • Super-resolution image reconstruction method using analysis sparse representation
  • Super-resolution image reconstruction method using analysis sparse representation
  • Super-resolution image reconstruction method using analysis sparse representation

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Embodiment Construction

[0064] The super-resolution image reconstruction method based on analytical sparse representation proposed by the present invention is described in detail in conjunction with the accompanying drawings and embodiments as follows:

[0065] The embodiment of the super-resolution image reconstruction method based on analytical sparse representation of the present invention consists of two parts: dictionary training and super-resolution image reconstruction, and its flow is as follows figure 1 As shown, among them,

[0066] The first part of dictionary training includes the following steps:

[0067] 11) Set the training parameters, including the image magnification A required by the user (A>1, the specific value is specified according to actual needs, the value in this embodiment is 2), the high-resolution image block h S of size a1 and low-resolution image patch l S The size a2 is a1=A×a2 (the size of y is generally set within 20×20 pixels to ensure the effect and operation spee...

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Abstract

The invention relates to a super-resolution image reconstruction method based on analysis sparse representation, belonging to the technical field of image processing. The method comprises the following steps of: performing dictionary training according to a training sample set; and training a high-resolution dictionary and a low-resolution dictionary for an extracted feature; converting an image to be input from an RGB (Red, Green and Blue) space into a 1 alpha beta space and dividing into blocks of a same size; performing two kinds of operation on the blocks, wherein one is that each block is amplified by using the conventional amplification method and the other one is that an residual image of each block is extracted, sparse representation of the residual image in the low-resolution dictionary is calculated, and then the residual image is reconstructed in the high-resolution dictionary to obtain a reconstructed residual image; summarizing results of the two steps, converting back into the RGB space and performing back projection to obtain the reconstructed super-resolution image. According to the method, the image reconstruction noise can be obviously reduced, and detail features are kept; and meanwhile, the method has the advantages of easiness in operation and wide application.

Description

technical field [0001] The invention belongs to the technical field of image resolution enhancement, in particular to a super-resolution image reconstruction method using analytical sparse representation. Background technique [0002] In a large number of electronic imaging applications, high resolution images are often desired. High resolution means a high density of pixels in an image, providing more detail that is essential in many practical applications. For example, high-resolution medical images are very helpful for doctors to make correct diagnoses; using high-resolution satellite images, it is easy to distinguish similar objects from similar objects; if high-resolution images can be provided, patterns in computer vision The recognition performance will be greatly improved. Since the 1970s, charge-coupled devices (CCDs), CMOS image sensors have been widely used to capture digital images. Although these sensors are suitable for most imaging applications, current res...

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Application Information

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IPC IPC(8): G06T3/40G06T5/50G06K9/66
Inventor 宁强陈侃弋力范楚楚陆垚温江涛
Owner CHINACCS INFORMATION IND
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