Improved Weighted Non-Local Mean Filtering Algorithm for Laser Image Speckle Suppression

Abstract

Laser speckle noise caused by coherence between lasers greatly influences the produced image. In order to suppress the effect of laser speckles on images, in this paper we set up a combination of a laser-structured light module and an infrared camera to acquire laser images, and propose an improved weighted non-local mean (IW-NLM) filtering method that adopts an SSI-based adaptive h-solving method to select the optimal h in the weight function. The analysis shows that the algorithm not only denoises the laser image but also smooths pixel jumps in the image, while preserving the image details. The experimental results show that compared with the original laser image, the equivalent number of looks (ENL) index of the IW-NLM filtered image improved by 0.80%. The speckle suppression index (SSI) of local images dropped from 4.69 to 2.55%. Compared with non-local mean filtering algorithms, the algorithm proposed in this paper is an improvement and provides more accurate data support for subsequent image processing analysis.

Influence of Image Processing Method on Wavefront Reconstruction Accuracy of Large-Aperture Laser

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“…The pixel values of the spot image are directly processed via spatial filtering, such as mean filtering, median filtering, etc. [12,13]. However, the above method has a poor filtering effect on the image and low calculation accuracy of the centroid when the SNR of the spot image is low [14].…”

Fast Localization and High Accuracy Recognition of Tire Surface Embossed Characters Based on CNN

“…A common method of image enhancement is grayscale transformation. The principle can be understood as a template to scan each pixel in the original image and determine the maximum and minimum of the grayscale values of the pixels in the template, making this difference the value of the pixel point at the center of the template [14,15]. Its main function is to overcome the contrast of the image and to overcome the exposure degree of insufficient or excessive exposure due to the imaging.…”

Non-Local Means Hole Repair Algorithm Based on Adaptive Block

“…Drawing inspiration from [15], this paper exploits the structural similarity between grayscale and depth images. It utilizes joint grayscale images to estimate depth values within hole regions and applies the non-local means algorithm [14][15][16][17][18][19][20][21] for effective hole repair. Successful restoration is achieved through the application of structural blocks and NLM-based hole filling.…”

“…(2) By introducing intelligent block factors, we enable the automatic determination of optimal search and repair patch sizes for voids of different dimensions, resulting in a significant reduction of the intricate debugging efforts in engineering applications. The strategy of improving the performance of the algorithm by manipulating the pixel weights is discussed in [5,[14][15][16][17]. Nonetheless, it is worth noting that the acquisition of these weights relies predominantly on manual calibration, a process that demands a substantial investment of time.…”