A Method of Image Noise Variance Estimation Based on Integer dct Transform

Abstract

The invention discloses an image noise variance estimation method based on integer DCT transformation. According to the resolution of the noisy image to be estimated, it is divided into non-overlapping image blocks of a certain size, and the divided image blocks are subjected to integer DCT transformation to obtain transformation coefficients. , according to the transformed AC coefficient as a measure of the uniformity of the image block, select the most uniform block according to a certain proportion among the obtained uniform blocks, and calculate the reference variance of the image noise; based on the reference variance of the image noise, search for uniform blocks again; obtain again For uniform blocks, the noise variance of the noisy image to be estimated is obtained according to the uniformity weighting process of the block. The integer DCT transformation of the present invention is easy to implement in hardware and is not limited to noisy images with specific characteristics. At the same time, the use of DC coefficients to correct the search interval of uniform blocks can improve the underestimation phenomenon caused by noise suppression due to overly bright or dark images. The present invention It is an image noise estimation method with high estimation accuracy and strong robustness.

Description

technical field [0001] The invention belongs to the field of digital image processing, in particular to an image noise estimation method based on integer DCT transformation. Background technique [0002] Image is a vivid, specific and effective information transmission medium. It is inevitable to introduce noise in the process of image acquisition and transmission. In order to restore the original real information of the image as much as possible, image denoising becomes the basis of other image preprocessing. Estimating the noise function model and its related parameters is one of the key tasks of image denoising in many image denoising methods. The noise model generally used is the Gauss model, because Gauss function noise is the most common in image noise, and the noise variance is an important indicator for evaluating noise. [0003] There are three types of image noise variance estimation methods commonly used: (1) Filtering method. Based on the smoothing filter pro...

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Problems solved by technology

[0005] The purpose of the present invention is to provide an image noise estimation method based on integer DCT transformation, aiming at solving the problem of underestimation in the current image noise variance estimation method when the image is too bright or too dark, and the calculation is complicated and not conducive to hardware implementation. The block method is highly dependent on the image's own characteristics and lacks robustness

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