数字农业图像在小波变换中信号滤波步骤

Agriculture Based on Digital Image Signal Filtering Step Wavelet Transform

对于传统数字农业在信号处理过程中经常首先将含有杂波噪声污染的信号进行傅立叶变换,然后经过滤波组装置操作后,再对其进行逆傅立叶变换得到较为"纯净地"信号,但是在滤波操作过程中;由于低通滤波平滑的作用,消除高频噪声的瞬间会使得边缘信息与纹理特征发生突变或冗余,这将在一定程度上对图像滤波的处理造成负面影响,从而影响图像处理数据真实性与可靠性;本文将从图像的去噪、压缩、增强三方面出发深入详细介绍图像高频与低频滤通的全过程;这将对进一步了解农业图像传输具有重要作用。

For a conventional digital signal processing in the signal agriculture often contain clutter noise pollution first performs a Fourier transformation,and then after filtering apparatus operation group,then its inverse Fourier transform more'purely' signal,but the filtering operation process;because of the low-pass filter smoothing effect,and instantly eliminate high-frequency noise will make the edge information and the texture characteristic mutation or redundant,to a certain extent this will have a negative impact on the image filtering process,thereby affecting the image data processing this article from the image de-noising,compression,enhancement departure three whole process of in-depth detailed images of high and low pass filter;authenticity and reliability which will transfer the image to learn more about agriculture plays an important role.