Image extraction in DCT domain

Feng, Guocan; Jiang, Jianmin

doi:10.1049/ip-vis:20030157

Cited by 14 publications

(2 citation statements)

References 12 publications

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“…As shown in Fig. 11(a), the recall ratio R is: 24 100% 80% 30  (17) The precision ratio P is: 24 100% 80% 30  (18) As shown in Fig. 11(b), the recall ratio R is: 30 100% 100% 30  (19) The precision ratio P is: 30 100% 100% 30  (20) Thus, the algorithm we proposed can improve retrieval accuracy.…”

Section: A Experimental Results and Analysis Based On Dct Compressedmentioning

confidence: 90%

Grading Image Retrieval Based on DCT and DWT Compressed Domains Using Low-Level Features

Wang¹,

Zhang²,

Shan³

et al. 2015

JCM

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Nowadays, the majority of images are in JPEG and MPEG compressed formats, and JPEG2000 is considered to be the next generation of compression standard due to the highperformance of discrete wavelet transform (DWT). It is timeconsuming and occupies too much memory in conventional image retrieval ways. In order to solve these problems, we use grading retrieval techniques to implement image retrieval based on discrete cosine transform (DCT) compressed domain and DWT compressed domain. For image retrieval based on DCT domain, we use color features: color moment and color histogram, to describe content of images and propose a new dynamic color space quantization based on color distribution; For image retrieval based on DWT domain, we use texture features as two level feature vectors. The mean and standard deviation of low frequency sub-band coefficients are used as the first level retrieval. The means and standard deviations of selected high frequency sub-band coefficients are used as the second level retrieval. Furthermore, the third level retrieval is achieved by the fast wavelet histogram. Our experiment results clearly show that the two grading image retrieval algorithms work better than other algorithms: store memory is reduced and retrieval accuracy is improved. Index Terms-Content based image retrieval (CBIR), compressed domain, discrete cosine transform (DCT), discrete wavelet transform (DWT), color features, texture features

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Section: A Experimental Results and Analysis Based On Dct Compressedmentioning

confidence: 90%

Grading Image Retrieval Based on DCT and DWT Compressed Domains Using Low-Level Features

Wang¹,

Zhang²,

Shan³

et al. 2015

JCM

View full text Add to dashboard Cite

show abstract

“…기반으로 압축된 동영상의 효과적인 탐색에 사용되고 있다 [7][8][9][10] . 블록단위의 DCT 부호화로 부호화된 동영상에서 축소 영상을 추출하는 대표적인 방법은 DCT 공간에서 DC 계수 를 직접 추출하는 방법이다.…”

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An Efficient Error Compensation Method for Thumbnail Extraction in H.264/AVC Bitstreams

Yoon

Lee²,

Sohn³

et al. 2008

Journal of Broadcast Engineering

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Recently, high definition media services like HDTV and IPTV are growing. A fast reduced-size image extracting method is required to meet what those services require. Conventional DC image extracting methods, however, can't be applied to H.264/AVC streams since a spatial domain prediction scheme is adopted in H.264/AVC intra mode. To solve this problem, a thumbnail extraction method in H.264/AVC was proposed. However, the method has mismatch problem which was caused by round-off operation in intra prediction and mismatch between integer and floating point calculation. In this paper, we propose an error compensation method for extracting thumbnail directly in H.264/AVC bitstreams. The compensation method introduces the mismatch problem in thumbnail extraction and presents compensation values. Through the implementation and performance evaluation, proposed method compensated round-off error efficiently in D1 and HD sequences while the additional extraction time is negligible.

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Pseudo-stereo Conversion from 2D Video

Feng

Jiang

2005

Advanced Concepts for Intelligent Vision Systems

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Image extraction in DCT domain

Cited by 14 publications

References 12 publications

Grading Image Retrieval Based on DCT and DWT Compressed Domains Using Low-Level Features

Grading Image Retrieval Based on DCT and DWT Compressed Domains Using Low-Level Features

An Efficient Error Compensation Method for Thumbnail Extraction in H.264/AVC Bitstreams

Pseudo-stereo Conversion from 2D Video

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