De‐noising method of aquatic product image with foreign matters based on improved wavelet transform and bilateral filter

Author:

Zhang Chunyan1,Li Xinxing12ORCID

Affiliation:

1. College of Information and Electrical Engineering China Agricultural University Beijing People's Republic of China

2. Nanchang Institute of Technology Nanchang People's Republic of China

Abstract

AbstractAiming at the strong spot noise caused by the reflection of meat slices in fish image with foreign matters that collected by ordinary camera or Single Lens Reflex (SLR) camera, we proposed an improved wavelet transform and bilateral filtering algorithm to reduce the noise of image. In this paper, our algorithm absorbed the advantages of wavelet threshold de‐noising algorithm and bilateral filtering algorithm, the wavelet threshold de‐noising algorithm being used for high frequency components and bilateral filtering being used for low frequency components, which not only achieved the effect of eliminating noise and weakening light spot, but also protected the details of the image. In the experiment, in order to verify the effectiveness of the proposed algorithm, we used the traditional bilateral filtering, Gaussian filtering and median filtering algorithms to process 500 salmon fish images which had residual fishbone, respectively. Since the original image itself was a noisy image, it was impossible to evaluate the noise reduction effect by using an algorithm that requires a noiseless image as a reference image, so we used five methods to evaluate the quality of the image processed by each algorithm, which were Blind/Referenceless Image Spatial QUality Evaluator (BRISQE), Cumulative Probability of Blur Detection (CPBD), variance, image entropy, and operation speed. Among them, BRISQE and CPBD could quantitatively reflect the overall quality of the image, the lower the BRISQE score or the higher the CPBD score, the better the quality of the image. Compared with other algorithms, the BRISQE score and CPBD score of the image processed by our algorithm were the best, with the average scores reaching 20.65 and .8421, respectively. Experimental results showed that the improved algorithm in this paper can effectively eliminate this kind of strong spot noise. The processed image has achieved better visual effect in both subjective and objective level.

Funder

Ministry of Science and Technology of the People's Republic of China

Publisher

Wiley

Subject

General Chemical Engineering,Food Science

Reference36 articles.

1. Spatially adaptive thresholding in wavelet domain for despeckling of ultrasound images

2. Research on tobacco foreign body detection device based on machine vision

3. Acceleration of the Shiftable $\mbi{O}{(1)}$ Algorithm for Bilateral Filtering and Nonlocal Means

4. Chen X. Wang Y. &Liu L.(2012). Deep study on wavelet threshold method for image noise removing.Laser & Infrared 42(1) 6 (in Chinese).

5. Chen Y. Xu H. Xing Q. &Zhuang J.(2022). A denoising algorithm for SICM image based on wavelet and bilateral filtering.Electronic Measurement Technology 45(in Chinese).

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