The purpose of this paper is to address the problem of difficulty in denoising after acquiring images in crop digital image processing. This paper introduces a median filtering method using wavelet transform to effectively solve the application of denoising algorithms in crop image processing. Through the lack of effective analysis of traditional denoising algorithms on the propagation characteristics of signals and noise in different decomposition layers, the basic principle of the lifting method is introduced, and the implementation method of constructing traditional wavelets using the lifting principle is given. Daubechies (9/7) lifting format wavelet is applied to the two-dimensional image denoising process, and a white color block processing is performed on the horizontal, vertical, and diagonal high-frequency coefficient matrices at each level after wavelet decomposition. Adaptive threshold denoising method. Compared with traditional algorithms, the method in this paper is simple to calculate, improves the operation speed by 50%, and increases the denoising effect by 64%. It improves the peak signal-to-noise ratio (PSNR) and minimum mean square error (MSE) of the image, and it is better Ground retains the texture and details of the image.

Linyuan Fan. New Denoising Algorithm in Crop Image Processing. International Journal of Neural Network (2022), Vol. 3, Issue 1: 30-41. https://doi.org/10.38007/NN.2022.030103.

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