Peppers denoising results with noise variance of 0.06.

<p>(a) Bilateral. (b) NLM. (c) Kuan. (d) Lee. (e) Lee-Enhanced. (f) Lee-Sigma. (g-i) 3D-NLE-BF with inputs of 2, 4, and 6 auxiliary images.</p>

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Bibliographic Details
Main Author:	Haiyan Zhang (176919) (author)
Other Authors:	Yang Liu (4829) (author), Guoyin Cai (9922178) (author)
Published:	2025
Subjects:	Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified reducing image contrast extensive imaging range evaluated using enl blurring edge contours uniform filtering approach multiplicative noise common addressing additive noise low spatial resolution image denoising due algorithm incorporates range sar images vary neighboring pixels based denoised pixels contain multitemporal sar data weak noise pixels neighboring pixel information neighboring pixels weak noise sar images multitemporal sar filtering efficacy extraneous data denoised based pixels along noise levels noise content free pixels filtered pixels xlink "> widely employed weighted average useful information target pixel surface features spatial stability significant variations selected bilateral relying solely pixel within less effective information loss information expressed higher similarity grayscale distances general applicability considerable amount comparison algorithms bilateral filter bf ). algorithm proposed algorithm capitalizes algorithm begins
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