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Article: New feature-preserving filter algorithm based on a priori knowledge of pixel types
Title | New feature-preserving filter algorithm based on a priori knowledge of pixel types |
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Authors | |
Keywords | Noise removal Feature preservation Corrupted pixel identification Impulse white noise Noise estimation |
Issue Date | 1996 |
Publisher | S P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oe |
Citation | Optical Engineering, 1996, v. 35 n. 12, p. 3508-3521 How to Cite? |
Abstract | The concept and algorithmic details of a new corrupted-pixel-identification- (CPI)-based estimation filter are presented. The approach is by transforming a noisy subimage centered on a corrupted pixel into its discrete cosine transform (DCT) domain, and approximating the transformed subimage by its DC (average) coefficient only, an estimation of the noise distribution is made by combining the knowledge of the number of corrupted pixels in the subimage and the pixel intensity of the noise term. This enables the DC coefficient of the restored image in the DCT domain to be determined, and from this, the restored pixel intensity can be calculated by an inverse DCT. The whole restored image can be obtained after all the corrupted pixels are exhausted. From an extensive performance evaluation, it was found that the new algorithm has a number of desirable characteristics. First, the CPI-based estimation algorithm performs extremely well when heavily degraded images are concerned. Second, the CPI-based estimation algorithm has acceptable feature-preserving properties, far better than the conventional median filter. Third, the new algorithm can be applied iteratively to the same noisy image. Fourth, the computing speed of the CPI-based estimation algorithm is almost three times faster than the conventional median filter, and 1.6 times faster than the original CPI algorithm, making it the fastest algorithm in this class so far. ©1996 Society of Photo – Optical Instrumentation Engineers. |
Persistent Identifier | http://hdl.handle.net/10722/42739 |
ISSN | 2023 Impact Factor: 1.1 2023 SCImago Journal Rankings: 0.331 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Lai, AHS | en_HK |
dc.contributor.author | Yung, NHC | en_HK |
dc.date.accessioned | 2007-03-23T04:31:14Z | - |
dc.date.available | 2007-03-23T04:31:14Z | - |
dc.date.issued | 1996 | en_HK |
dc.identifier.citation | Optical Engineering, 1996, v. 35 n. 12, p. 3508-3521 | en_HK |
dc.identifier.issn | 0091-3286 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/42739 | - |
dc.description.abstract | The concept and algorithmic details of a new corrupted-pixel-identification- (CPI)-based estimation filter are presented. The approach is by transforming a noisy subimage centered on a corrupted pixel into its discrete cosine transform (DCT) domain, and approximating the transformed subimage by its DC (average) coefficient only, an estimation of the noise distribution is made by combining the knowledge of the number of corrupted pixels in the subimage and the pixel intensity of the noise term. This enables the DC coefficient of the restored image in the DCT domain to be determined, and from this, the restored pixel intensity can be calculated by an inverse DCT. The whole restored image can be obtained after all the corrupted pixels are exhausted. From an extensive performance evaluation, it was found that the new algorithm has a number of desirable characteristics. First, the CPI-based estimation algorithm performs extremely well when heavily degraded images are concerned. Second, the CPI-based estimation algorithm has acceptable feature-preserving properties, far better than the conventional median filter. Third, the new algorithm can be applied iteratively to the same noisy image. Fourth, the computing speed of the CPI-based estimation algorithm is almost three times faster than the conventional median filter, and 1.6 times faster than the original CPI algorithm, making it the fastest algorithm in this class so far. ©1996 Society of Photo – Optical Instrumentation Engineers. | en_HK |
dc.format.extent | 2318423 bytes | - |
dc.format.extent | 5183 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | text/plain | - |
dc.language | eng | en_HK |
dc.publisher | S P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oe | en_HK |
dc.relation.ispartof | Optical Engineering | - |
dc.rights | Copyright 1996 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. This article is available online at https://doi.org/10.1117/1.601087 | - |
dc.subject | Noise removal | en_HK |
dc.subject | Feature preservation | en_HK |
dc.subject | Corrupted pixel identification | en_HK |
dc.subject | Impulse white noise | en_HK |
dc.subject | Noise estimation | en_HK |
dc.title | New feature-preserving filter algorithm based on a priori knowledge of pixel types | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0091-3286&volume=35&issue=12&spage=3508&epage=3521&date=1996&atitle=New+feature-preserving+filter+algorithm+based+on+a+priori+knowledge+of+pixel+types | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.doi | 10.1117/1.601087 | en_HK |
dc.identifier.scopus | eid_2-s2.0-0003969755 | - |
dc.identifier.hkuros | 26671 | - |
dc.identifier.volume | 35 | - |
dc.identifier.issue | 12 | - |
dc.identifier.spage | 3508 | - |
dc.identifier.epage | 3521 | - |
dc.identifier.isi | WOS:A1996VX10000022 | - |
dc.identifier.issnl | 0091-3286 | - |