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FPGA based spliced image speckle noise eliminating method and device

A technology for splicing images and speckle noise, applied in the field of image processing, can solve problems such as insufficient real-time performance, high cost, and reduced image resolution, and achieve high real-time transmission processing speed and cost-saving effects.

Inactive Publication Date: 2015-07-01
深圳市巨烽显示科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The technical problem to be solved by the embodiments of the present invention is to provide an FPGA-based mosaic image speckle noise elimination technology for the defects of reduced image resolution, insufficient real-time performance, and high cost in the prior art. The method and device will not affect the resolution of the image, the real-time tracking performance is better, and the cost is lower

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  • FPGA based spliced image speckle noise eliminating method and device
  • FPGA based spliced image speckle noise eliminating method and device
  • FPGA based spliced image speckle noise eliminating method and device

Examples

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no. 1 example

[0051] See figure 1 , is the flow chart of the first embodiment of the method for eliminating speckle noise in spliced ​​images based on FPGA provided by the present invention, and the method includes:

[0052] S101. In the FPGA, read the source mosaic image. For example, if the source mosaic image has N horizontal sampling points and M vertical sampling points, the image can be stitched for each source in DDR SDRAM (Double Data Rate Synchronous Dynamic Random Access Memory) of the FPGA Apply for an array Data[M][N] with a size of M*N respectively, which is used to cache the read pixel S(i,j) in the mosaic image of the road source, where i=0, 1,..., M-1, j=0, 1, ..., N-1, M, N are all natural numbers greater than zero.

[0053] S102. Generate filter windows centered on the pixels in the source stitched image in sequence, and calculate the mean value, absolute difference and mean value of each filter window respectively. The filter window can be square or rectangular, but in...

no. 2 example

[0057] See figure 2 , is the flowchart of the second embodiment of the FPGA-based mosaic image speckle noise elimination method provided by the present invention, the method comprising:

[0058] S201. Set a filter window size factor K, where K is a natural number greater than zero.

[0059] S202. In the FPGA, read the pixel S(i,j) of the source mosaic image. For example, if the source mosaic image has N horizontal sampling points and M vertical sampling points, M and N are both natural numbers greater than zero, you can apply for a size of M*N for each source mosaic image in the FPGA's DDR SDRAM. Array Data[M][N] to store the read pixel S(i,j) in the mosaic image of the road source. Wherein i=0, 1,..., M-1, j=0, 1,..., N-1, M and N are both natural numbers greater than zero.

[0060] S203. Generating a square filter window C centered on the pixels in the source stitched image in sequence i,j , the side length of the square filter window is 2K+1. For example, for pixel S(...

no. 3 example

[0065] See image 3 , is the flowchart of the third embodiment of the method for eliminating speckle noise in spliced ​​images based on FPGA provided by the present invention, and the method includes:

[0066] S301. Set the filter window size factor K and the filter window center weight coefficient W 中心 and scale factor α, where K is a natural number greater than zero.

[0067]S302. In the FPGA, read the pixel S(i, j) of the source mosaic image. For example, if the source mosaic image has N horizontal sampling points and M vertical sampling points, and both M and N are natural numbers greater than zero, you can apply for each source mosaic image in the FPGA's DDR SDRAM with a size of M*N. The array Data[M][N] is used to store the read pixel S(i,j) in the mosaic image of the road source. Wherein i=0, 1,..., M-1, j=0, 1,..., N-1, M and N are both natural numbers greater than zero.

[0068] S303. Generate a square filter window C centered on the pixels in the source stitched ...

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Abstract

The embodiment of the invention discloses an FPGA based spliced image speckle noise eliminating method and device. The FPGA based spliced image speckle noise eliminating method comprises the steps of reading source spliced images in an FPGA; using pixels of the source spliced images as centers to generate filter windows and respectively calculating a mean value of each filter window and absolute difference and a mean value; respectively calculating weighting coefficients of the pixels in the filter windows according to the mean value of each filter window and the absolute difference and the mean value; respectively calculating weighting mil-values of the filter windows according to the weighting coefficients of the pixels in the filter windows to obtain output spliced images without speckle noise. Frame related processing is not needed, so that the invention discloses an FPGA based spliced image speckle noise eliminating method and device are achieved by adopting pure hardware and have higher real-time transmission processing speed, cost is saved, and meanwhile no advance influence is produced on image definition.

Description

technical field [0001] The present invention relates to the field of image processing, in particular to an FPGA (Field Programmable Gate Array, Field Programmable Gate Array)-based splicing image speckle noise elimination method and device. Background technique [0002] The research on the statistical properties of speckle noise shows that the common speckle noise obeys the Rayleigh distribution, and its mean value is proportional to the standard deviation, which shows that the speckle noise is multiplicative. However, in the process of image mosaic, since there are N signal inputs, the signal may be processed by scaling, logarithmic compression, low-pass filtering, and interpolation operations, thereby changing the statistical characteristics of the original signal, and its mean value is no longer Not proportional to the standard deviation, but proportional to the variance. According to this characteristic, Loupas et al. proposed a more complex statistical model of speckle...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50
Inventor 张雄林恩礼徐斌林武林阳辉彭昊
Owner 深圳市巨烽显示科技有限公司
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