Image block effect removing method on basis of curvelet transformation

A technology of deblocking and curvelet transform, applied in the field of image processing, can solve the problem that the details of the image do not have a good restoration effect, and achieve a good practical effect

Inactive Publication Date: 2012-06-27
NANJING UNIV
View PDF2 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The subsequent deblocking algorithm based on wavelet transform, although simple and fast, has a good restoration effect on the smooth area of ​​the image, but it still has no good restoration effect on the details of the image.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image block effect removing method on basis of curvelet transformation
  • Image block effect removing method on basis of curvelet transformation
  • Image block effect removing method on basis of curvelet transformation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] Such as Figure 4 As shown, the present invention discloses a method for image deblocking effect based on curvelet transform, comprising the following steps:

[0027] Step 1, performing curvelet transform on the target image to obtain scale levels and curvelet coefficients of each level: use curvelet transform to divide the image into scale levels, and analyze the curvelet coefficients of each level;

[0028] Described step one comprises the following steps:

[0029] Step (11), performing curvelet transform on the target image; including dividing the image into a coarse layer (Coarse Layer), a detail layer (Detail Layers), and a fine layer (Fine Layer) by curvelet transform.

[0030] Assuming that the image size is N×N, the number of scale levels divided by the curvelet coefficients is:

[0031] scale=log 2 (N)-3

[0032] The curvelet coefficient is C{j}{l}(k1, k2), where j represents the scale, l represents the direction, and (k1, k2) represents the coordinates of ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an image block effect removing method on the basis of curvelet transformation, which comprises the following steps of: step 1, carrying out curvelet transformation on a target image to obtain scale levels and a curvelet coefficient of each level; step 2, finding a layer which is furthest influenced by a block effect and processing the layer; and step 3, recovering the image. According to the invention, the curvelet transformation is utilized to carry out layered processing on the image; the recovered image is reconstructed by a novel coefficient matrix; and compared with a conventional block effect removing method, the image block effect removing method disclosed by the invention has a better recovery effect on the aspects of both subjective and objective evaluation.

Description

technical field [0001] The invention relates to the field of image processing, mainly relates to image deblocking processing and reconstruction, in particular to an image deblocking method based on curvelet transform. Background technique [0002] At present, block discrete cosine transform (BDCT) is adopted as the core compression algorithm by most current international image and video compression standards. The algorithm divides the image into multiple 8x8 pixel blocks, uses the discrete cosine transform (DCT) to transform each block from the spatial domain to the frequency domain, and performs individual quantization and coding. However, since these blocks are coded separately, the correlation of pixels in adjacent blocks is not considered, so the quantization is rough when encoding at low bit rates, and the DCT coefficients of adjacent blocks fall in different quantization intervals, resulting in the occurrence of block effect. [0003] At present, the deblocking algor...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T5/00
Inventor 袁杰邵真天何雨兰顾人舒朱毅
Owner NANJING UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products