CN107481193A - A kind of image interpolation method based on wavelet transformation - Google Patents
A kind of image interpolation method based on wavelet transformation Download PDFInfo
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- CN107481193A CN107481193A CN201710717386.1A CN201710717386A CN107481193A CN 107481193 A CN107481193 A CN 107481193A CN 201710717386 A CN201710717386 A CN 201710717386A CN 107481193 A CN107481193 A CN 107481193A
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- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000001678 elastic recoil detection analysis Methods 0.000 claims abstract description 16
- 230000003321 amplification Effects 0.000 claims abstract description 13
- 238000003199 nucleic acid amplification method Methods 0.000 claims abstract description 13
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 11
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4007—Scaling of whole images or parts thereof, e.g. expanding or contracting based on interpolation, e.g. bilinear interpolation
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Abstract
The present invention discloses a kind of image interpolation method based on wavelet transformation, comprises the following steps：S101, interpolation amplification, acquisition original image are carried out to original low-resolution image using weighted parabolic interpolation error compensation；S102, wavelet transformation decomposition is carried out to the original image, obtain a low frequency part and some HFSs；S103, to after the original image wavelet decomposition HFS retain it is constant；S104, according to obtain new low frequency part and image wavelet decompose after HFS carry out the image after wavelet inverse transformation acquisition processing.Not only complexity is low by the present invention, and smoothing function is good, and LPF property is not present, and the image clearly of processing is natural.
Description
Technical field
The present invention relates to image processing field, more particularly to a kind of image interpolation method based on wavelet transformation.
Background technology
Image interpolation is exactly to produce the gray value of unknown pixel using the gray value of known neighborhood pixels, so as to by source figure
As producing the image with higher resolution.Traditional image interpolation method lays particular emphasis on the smooth of image, more preferable to obtain
Visual effect, but this kind of method frequently results in the edge blurry of image while image smoothing is kept, and the edge of image is believed
Breath is an important factor for influenceing visual effect.A kind of simplest interpolation method, four in interpolation pixel of closest method
In adjacent pixel, the gray value of the adjacent pixel nearest apart from interpolation pixel is assigned to interpolation pixel.Bilinear interpolation side
Method is more complicated than closest method, but has smoothing function, can be efficiently against the deficiency of closest method, but has low pass filtered
Wave property, the HFS of image can be caused to degenerate so that the details of image thickens.
The content of the invention
It is an object of the invention to by a kind of image interpolation method based on wavelet transformation, to solve background above technology
The problem of part is mentioned.
To use following technical scheme up to this purpose, the present invention：
A kind of image interpolation method based on wavelet transformation, it comprises the following steps：
S101, interpolation amplification, acquisition original are carried out to original low-resolution image using weighted parabolic interpolation error compensation
Beginning image；
S102, wavelet transformation decomposition is carried out to the original image, obtain a low frequency part and some HFSs；
S103, to after the original image wavelet decomposition HFS retain it is constant；
S104, according to obtain new low frequency part and image wavelet decompose after HFS carry out wavelet inverse transformation and obtain
Image after must handling.
Especially, the step S101 is specifically included：Using weighted parabolic interpolation error compensation to original low-resolution
Image carries out interpolation amplification, obtains original image；Image is subjected to interpolation amplification, the click-through row interpolation in original image row or column
Amplification, estimates for the point on diagonal.
Especially, the step S103 is specifically included：HFS after the original image wavelet decomposition is retained
It is constant；Linear transformation is carried out to original low-resolution image, utilizes the adaptive width of wavelet coefficient and numerical relation of low frequency part
Degree enhancing, obtains new low frequency part.
Image interpolation method complexity proposed by the present invention based on wavelet transformation is low, and smoothing function is good, in the absence of low pass
Filtering property, the image clearly of processing are natural.
Brief description of the drawings
Fig. 1 is the image interpolation method flow chart provided in an embodiment of the present invention based on wavelet transformation.
Embodiment
The invention will be further described with reference to the accompanying drawings and examples.It is understood that tool described herein
Body embodiment is used only for explaining the present invention, rather than limitation of the invention.It also should be noted that for the ease of retouching
State, part related to the present invention rather than full content are illustrate only in accompanying drawing, it is unless otherwise defined, used herein all
Technology and scientific terminology are identical with belonging to the implication that the those skilled in the art of the present invention are generally understood that.It is used herein
Term be intended merely to describe specific embodiment, it is not intended that in limitation the present invention.
It refer to shown in Fig. 1, Fig. 1 is the image interpolation method flow provided in an embodiment of the present invention based on wavelet transformation
Figure.
The image interpolation method based on wavelet transformation specifically comprises the following steps in the present embodiment：
S101, interpolation amplification, acquisition original are carried out to original low-resolution image using weighted parabolic interpolation error compensation
Beginning image.Interpolation amplification is carried out to original low-resolution image using weighted parabolic interpolation error compensation in the present embodiment,
Obtain original image；Image is subjected to interpolation amplification, the click-through row interpolation amplification in original image row or column, on diagonal
Point estimated.
S102, wavelet transformation decomposition is carried out to the original image, obtain a low frequency part and some HFSs.
S103, to after the original image wavelet decomposition HFS retain it is constant.In the present embodiment to described
HFS after original image wavelet decomposition retains constant；Linear transformation is carried out to original low-resolution image, utilization is low
The adaptive amplitude enhancing of wavelet coefficient and numerical relation of frequency part, obtains new low frequency part.
S104, according to obtain new low frequency part and image wavelet decompose after HFS carry out wavelet inverse transformation and obtain
Image after must handling.
Image interpolation method complexity proposed by the present invention based on wavelet transformation is low, and smoothing function is good, in the absence of low pass
Filtering property, the image clearly of processing are natural.The preferred embodiments of the present invention are the foregoing is only, are not limited to this hair
Bright, to those skilled in the art, the present invention can have various changes and change.It is all spirit and principles of the present invention it
Interior made any modification, equivalent substitution and improvements etc., should be included in the scope of the protection.
One of ordinary skill in the art will appreciate that realize all or part of flow in above-described embodiment method, being can be with
The hardware of correlation is instructed to complete by computer program, described program can be stored in a computer read/write memory medium
In, the program is upon execution, it may include such as the flow of the embodiment of above-mentioned each method.Wherein, described storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random Access
Memory, RAM) etc..
Claims (3)
1. a kind of image interpolation method based on wavelet transformation, it is characterised in that it comprises the following steps：
S101, interpolation amplification, acquisition original graph are carried out to original low-resolution image using weighted parabolic interpolation error compensation
Picture；
S102, wavelet transformation decomposition is carried out to the original image, obtain a low frequency part and some HFSs；
S103, to after the original image wavelet decomposition HFS retain it is constant；
S104, according to obtain new low frequency part and image wavelet decompose after HFS carry out at wavelet inverse transformation acquisition
Image after reason.
2. the image interpolation method according to claim 1 based on wavelet transformation, it is characterised in that the step S101 tools
Body includes：Interpolation amplification is carried out to original low-resolution image using weighted parabolic interpolation error compensation, obtains original image；
Image is subjected to interpolation amplification, the click-through row interpolation amplification in original image row or column, estimated for the point on diagonal.
3. the image interpolation method according to claim 2 based on wavelet transformation, it is characterised in that the step S103 tools
Body includes：HFS after the original image wavelet decomposition is retained constant；Line is entered to original low-resolution image
Property conversion, strengthened using the adaptive amplitude of the wavelet coefficient and numerical relation of low frequency part, obtain new low frequency part.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108090874A (en) * | 2017-12-29 | 2018-05-29 | 努比亚技术有限公司 | A kind of processing method of image border, terminal and storage medium |
| CN108446440A (en) * | 2018-02-11 | 2018-08-24 | 上海理工大学 | The method for improving particle temperature measurement accuracy |
| CN109283590A (en) * | 2018-08-29 | 2019-01-29 | 国家海洋局第海洋研究所 | Multi-source gravimetric data fusion method based on wavelet transformation |
| CN110967717A (en) * | 2019-12-23 | 2020-04-07 | 合肥工业大学 | Cycle slip detection and restoration method based on wavelet transform method |
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| US20020032896A1 (en) * | 2000-09-14 | 2002-03-14 | Masanori Fukuda | Circuit design method and circuit design apparatus |
| CN103500436A (en) * | 2013-09-17 | 2014-01-08 | 广东威创视讯科技股份有限公司 | Image super-resolution processing method and system |
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2017
- 2017-08-21 CN CN201710717386.1A patent/CN107481193A/en not_active Withdrawn
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020032896A1 (en) * | 2000-09-14 | 2002-03-14 | Masanori Fukuda | Circuit design method and circuit design apparatus |
| CN103500436A (en) * | 2013-09-17 | 2014-01-08 | 广东威创视讯科技股份有限公司 | Image super-resolution processing method and system |
| CN105046651A (en) * | 2015-08-04 | 2015-11-11 | 深圳信息职业技术学院 | Super-resolution reconstruction method and apparatus for image |
Non-Patent Citations (1)
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| 刘馨月等: "基于加权抛物线插值与小波变换的图像放大算法", 《计算机工程与应用》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108090874A (en) * | 2017-12-29 | 2018-05-29 | 努比亚技术有限公司 | A kind of processing method of image border, terminal and storage medium |
| CN108446440A (en) * | 2018-02-11 | 2018-08-24 | 上海理工大学 | The method for improving particle temperature measurement accuracy |
| CN109283590A (en) * | 2018-08-29 | 2019-01-29 | 国家海洋局第海洋研究所 | Multi-source gravimetric data fusion method based on wavelet transformation |
| CN110967717A (en) * | 2019-12-23 | 2020-04-07 | 合肥工业大学 | Cycle slip detection and restoration method based on wavelet transform method |
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Application publication date: 20171215 |