Salt-and-pepper Noise Reduction for Medical Images Based on Image Fusion

During the collection process, the prostate capsule is prone to introduce salt and pepper noise due to gastrointestinal peristalsis, which will affect the precision of subsequent object detection.

A cascade optimization scheme for image denoising based on image fusion was proposed to improve the peak signal-to-noise ratio(PSNR) and contour protection performance of heterogeneous medical images after image denoising.

Anisotropic diffusion fusion (ADF) was used to decompose the images denoised by adaptive median filter, non-local adaptive median filter and artificial neural network to generate the base layer and detail layer, which were fused by weighted average and Karhunen-Loeve Transform respectively. Finally, the image was reconstructed by linear superposition.

Compared with the traditional denoising method, the image denoised by this method has a higher PSNR while maintaining the image edge contour.

Using the denoised dataset for object detection, the detection precision of the obtained model is higher.