{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T23:22:05Z","timestamp":1784676125412,"version":"3.55.0"},"reference-count":17,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2018,7,13]],"date-time":"2018-07-13T00:00:00Z","timestamp":1531440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61372156"],"award-info":[{"award-number":["61372156"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Parameter estimation of Poisson-Gaussian signal-dependent random noise in the complementary metal-oxide semiconductor\/charge-coupled device image sensor is a significant step in eliminating noise. The existing estimation algorithms, which are based on finding homogeneous regions, acquire the pair of the variances of noise and the intensities of every homogeneous region to fit the linear or piecewise linear curve and ascertain the noise parameters accordingly. In contrast to the existing algorithms, in this study, the Poisson noise samples of all homogeneous regions in every block image are pieced together to constitute a larger sample following the mixed Poisson noise distribution; then, the mean and variance of the mixed Poisson noise sample are deduced. Next, the mapping function among the noise parameters to be estimated\u2014variance of Poisson-Gaussian noise and that of Gaussian noise corresponding to the stitched region in every block image\u2014is constructed. Finally, the unbiased estimations of noise parameters are calculated from the mapping functions of all the image blocks. The experimental results confirm that the proposed method can obtain lower mean absolute error values of estimated noise parameters than the conventional ones.<\/jats:p>","DOI":"10.3390\/s18072276","type":"journal-article","created":{"date-parts":[[2018,7,16]],"date-time":"2018-07-16T04:05:33Z","timestamp":1531713933000},"page":"2276","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Parameter Estimation of Signal-Dependent Random Noise in CMOS\/CCD Image Sensor Based on Numerical Characteristic of Mixed Poisson Noise Samples"],"prefix":"10.3390","volume":"18","author":[{"given":"Yu","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Electronic and Information, Hangzhou Dianzi University, Hangzhou 310018, China"},{"name":"Key Laboratory for RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangyi","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic and Information, Hangzhou Dianzi University, Hangzhou 310018, China"},{"name":"Key Laboratory for RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiangtao","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Microelectronics, Tianjin University, Tianjin 300072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1737","DOI":"10.1109\/TIP.2008.2001399","article-title":"Practical Poissonian-Gaussian noise modeling and fitting for single-image raw data","volume":"17","author":"Foi","year":"2008","journal-title":"IEEE Trans. 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