國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Perceptual image coding with discret...

Gan, Woon-Seng.

Perceptual image coding with discrete cosine transform

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Perceptual image coding with discrete cosine transformby Ee-Leng Tan, Woon-Seng Gan.
作者:	Tan, Ee-Leng.
其他作者:	Gan, Woon-Seng.
出版者:	Singapore :Springer Singapore :2015.
面頁冊數:	viii, 69 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Computer scienceMathematics.
電子資源:	http://dx.doi.org/10.1007/978-981-287-543-3
ISBN:	9789812875433 (electronic bk.)

Perceptual image coding with discrete cosine transform
Tan, Ee-Leng.

Perceptual image coding with discrete cosine transform[electronic resource] /by Ee-Leng Tan, Woon-Seng Gan. - Singapore :Springer Singapore :2015. - viii, 69 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering. Signal processing,2191-8112. - SpringerBriefs in electrical and computer engineering.Signal processing..

Introduction -- Computational Models for Just-Noticeable-Differences -- Perceptual Image Coding with Discrete Cosine Transform -- Validation of Computational Model for JND -- Concluding Remarks.

This book first introduces classic as well as recent computational models for just-noticeable-difference (JND) applications. Since the discrete cosine transform (DCT) is applied in many image and video standards (JPEG, MPEG-1/2/4, H.261/3), the book also includes a comprehensive survey of computational models for JND that are based on DCT. The visual factors used in these computational models are reviewed in detail. Further, an extensive comparative analysis of these models using quantitative and qualitative performance criteria is presented, which compares the noise shaping performance of these models with subjective evaluation and the accuracy between the estimated JND thresholds and subjective evaluation. There are many surveys available on computational models for JND; however, these surveys seldom compare the performance of computational models that are based on DCT. The authors' survey of the computational models and their in-depth review of the visual factors used in them will help readers understand perceptual image coding based on DCT. The book also provides a comparative analysis of several perceptual image coders that are based on DCT, which are compatible with the highly popular and widely adopted JPEG standard.

ISBN: 9789812875433 (electronic bk.)

Standard No.: 10.1007/978-981-287-543-3doiSubjects--Topical Terms:

181991
Computer science
--Mathematics.

LC Class. No.: QA76.9.M35

Dewey Class. No.: 004.0151

Perceptual image coding with discrete cosine transform
LDR:02544nmm a2200349 a 4500 001 469092
003 DE-He213
005 20151229164110.0
006 m d
007 cr nn 008maaau
008 160118s2015 si s 0 eng d
020 $a 9789812875433 (electronic bk.)
020 $a 9789812875426 (paper)
024 7 $a 10.1007/978-981-287-543-3 $2 doi
035 $a 978-981-287-543-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.M35
072 7 $a TTBM $2 bicssc
072 7 $a UYS $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a COM073000 $2 bisacsh
082 0 4 $a 004.0151 $2 23
090 $a QA76.9.M35 $b T161 2015
100 1 $a Tan, Ee-Leng. $3 724922
245 1 0 $a Perceptual image coding with discrete cosine transform $h [electronic resource] / $c by Ee-Leng Tan, Woon-Seng Gan.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2015.
300 $a viii, 69 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in electrical and computer engineering. Signal processing, $x 2191-8112
505 0 $a Introduction -- Computational Models for Just-Noticeable-Differences -- Perceptual Image Coding with Discrete Cosine Transform -- Validation of Computational Model for JND -- Concluding Remarks.
520 $a This book first introduces classic as well as recent computational models for just-noticeable-difference (JND) applications. Since the discrete cosine transform (DCT) is applied in many image and video standards (JPEG, MPEG-1/2/4, H.261/3), the book also includes a comprehensive survey of computational models for JND that are based on DCT. The visual factors used in these computational models are reviewed in detail. Further, an extensive comparative analysis of these models using quantitative and qualitative performance criteria is presented, which compares the noise shaping performance of these models with subjective evaluation and the accuracy between the estimated JND thresholds and subjective evaluation. There are many surveys available on computational models for JND; however, these surveys seldom compare the performance of computational models that are based on DCT. The authors' survey of the computational models and their in-depth review of the visual factors used in them will help readers understand perceptual image coding based on DCT. The book also provides a comparative analysis of several perceptual image coders that are based on DCT, which are compatible with the highly popular and widely adopted JPEG standard.
650 0 $a Computer science $x Mathematics. $3 181991
650 0 $a Discrete cosine transforms. $3 724923
650 0 $a Signal processing. $3 182382
650 0 $a Image processing. $3 182627
650 0 $a Computer engineering. $3 212944
650 1 4 $a Engineering. $3 210888
650 2 4 $a Signal, Image and Speech Processing. $3 273768
650 2 4 $a Image Processing and Computer Vision. $3 274051
650 2 4 $a Discrete Mathematics in Computer Science. $3 274791
700 1 $a Gan, Woon-Seng. $3 266073
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in electrical and computer engineering. $p Signal processing. $3 674929
856 4 0 $u http://dx.doi.org/10.1007/978-981-287-543-3
950 $a Engineering (Springer-11647)