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Author: Oktem,R.Subject: [No Keyword Available]

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    Conference Object
    Citation - Scopus: 2
    Improving Compression Ratio for Satellite Transmission by Use of Cloud Extraction
    (2005) Oktem,R.; Benderli,O.; Ismailoǧlu,N.
    This paper presents an alternative approach to JPEG 2000 based ROI coding, for use on-board satellite image compression. The proposed method works in the wavelet domain and modifies the wavelet coefficients in a way to allocate fewer bits for cloud-covered areas. This approach improves compression ratio and/or improves the quality of un-cloud-covered areas. The algorithm is implemented with pixel based and codeblock based schemes. Pixel based scheme can be embedded into any wavelet transform based codec. Both schemes allow packing of the coefficients into a fully JPEG2000 decoder compatible bitstream as soon as a codeblock is formed. The performance of the proposed schemes are demonstrated by tests on real satellite images acquired by BILSAT I.
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    Article
    Citation - Scopus: 64
    Image filtering based on discrete cosine transform
    (2007) Lukin,V.V.; Oktem,R.; Ponomarenko,N.N.; Egiazarian,K.O.
    Quite often acquired images are noisy and filtering is a standard operation to improve image quality. "Good" filters should preserve details, edges and texture features and, at the same time, suppress noise. Recently it has been demonstrated that transform based filters are able to satisfy these requirements well enough and much attention has been paid to wavelet based filter design. In this paper it is shown that another kind of transform based filters, namely, discrete cosine transform (DCT) filters is an effective tool that competes with the state of the art methods. An additive noise case is basically considered although quite easily the DCT based filter can be modified for coping with other types of noise. © 2007 Begell House, Inc.
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    Conference Object
    Citation - Scopus: 2
    A Superresolution Approach for Bar Code Reading
    (2005) Oktem,R.; Oktem,L.
    This paper presents a computer vision based method for bar code reading. Bar code's geometric features and the imaging system parameters are jointly extracted from a tilted low resolution bar code image. This approach enables the use of cost effective cameras, increases the depth of acquisition, and provides solutions for cases where image quality is low. The performance of the algorithm is tested on synthetic and real test images, and extension to a 2D bar code (PDF417) is also discussed.