Bachoo, A2012-01-162012-01-162010-10Bachoo, A. 2010. Blind assessment of image blur using the Haar wavelet. 2010 Annual Research Conference of the South African Institute for Computer Scientists and Information Technologists (SAICSIT 2010), Bela Bela, South Africa, 11-13 October 2010, pp4http://hdl.handle.net/10204/54892010 Annual Research Conference of the South African Institute for Computer Scientists and Information Technologists (SAICSIT 2010), Bela Bela, South Africa, 11-13 October 2010Images and video captured in real world situations generally have distorted digital pixel values. A variety of situations can cause these image degradations: sensor motion, environmental conditions and random noise. A crucial procedure in computer vision is the assessment and quantification of digital image quality. A numerical score for describing image quality is useful for a number of applications, some of which include improving the performance of an image acquisition system and adaptive algorithms. We present an intuitive quality metric for characterizing the amount of blur in an image, through blind image assessment, using the Haar discrete wavelet transform. Thus, the method does not require a reference image or any prior information. The novelty of our method lies in processing the image derivative using the discrete wavelet transform rather than directly processing image intensity values as is traditionally done. We present late breaking results and analysis for a small set of data. The proposed method shows promise for a large number of avenues such as real- time blur level assessment and image depth of focus estimation.enImage blur characterizationHaar waveletBlind image qualityNo-reference imageConference PresentationBachoo, A. (2010). Blind assessment of image blur using the Haar wavelet. http://hdl.handle.net/10204/5489Bachoo, A. "Blind assessment of image blur using the Haar wavelet." (2010): http://hdl.handle.net/10204/5489Bachoo A, Blind assessment of image blur using the Haar wavelet; 2010. http://hdl.handle.net/10204/5489 .TY - Conference Presentation AU - Bachoo, A AB - Images and video captured in real world situations generally have distorted digital pixel values. A variety of situations can cause these image degradations: sensor motion, environmental conditions and random noise. A crucial procedure in computer vision is the assessment and quantification of digital image quality. A numerical score for describing image quality is useful for a number of applications, some of which include improving the performance of an image acquisition system and adaptive algorithms. We present an intuitive quality metric for characterizing the amount of blur in an image, through blind image assessment, using the Haar discrete wavelet transform. Thus, the method does not require a reference image or any prior information. The novelty of our method lies in processing the image derivative using the discrete wavelet transform rather than directly processing image intensity values as is traditionally done. We present late breaking results and analysis for a small set of data. The proposed method shows promise for a large number of avenues such as real- time blur level assessment and image depth of focus estimation. DA - 2010-10 DB - ResearchSpace DP - CSIR KW - Image blur characterization KW - Haar wavelet KW - Blind image quality KW - No-reference image LK - https://researchspace.csir.co.za PY - 2010 T1 - Blind assessment of image blur using the Haar wavelet TI - Blind assessment of image blur using the Haar wavelet UR - http://hdl.handle.net/10204/5489 ER -