Adaptive image coding based on the discrete wavelet transform

H. Jafarkhani; N. Farvardin; C. C. Lee

doi:10.1109/ICIP.1994.413830

Adaptive image coding based on the discrete wavelet transform

H. Jafarkhani
, N. Farvardin
, C. C. Lee

Department of Electrical and Computer Engineering

University of Maryland, College Park

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

In this paper we present an adaptive discrete wavelet transform image coding scheme. The main contribution of the work is in developing a simple classification procedure which is used to classify the subband blocks into a finite number of classes. The classified subband blocks are subsequently encoded. The low frequency band is encoded by means of a 2-D DCT using entropy-coded trellis coded quantization (ECTCQ); other bands are directly encoded using ECTCQ. The peak signal-to-noise ratio results of the proposed adaptive system are 0.4-1.0 dB superior to those of its non-adaptive counterpart.

Original language	English
Article number	413830
Pages (from-to)	343-347
Number of pages	5
Journal	Proceedings - International Conference on Image Processing, ICIP
Volume	3
DOIs	https://doi.org/10.1109/ICIP.1994.413830
State	Published - 1994
Event	The 1994 1st IEEE International Conference on Image Processing - Austin, TX, USA Duration: 13 Nov 1994 → 16 Nov 1994

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10.1109/ICIP.1994.413830

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title = "Adaptive image coding based on the discrete wavelet transform",

abstract = "In this paper we present an adaptive discrete wavelet transform image coding scheme. The main contribution of the work is in developing a simple classification procedure which is used to classify the subband blocks into a finite number of classes. The classified subband blocks are subsequently encoded. The low frequency band is encoded by means of a 2-D DCT using entropy-coded trellis coded quantization (ECTCQ); other bands are directly encoded using ECTCQ. The peak signal-to-noise ratio results of the proposed adaptive system are 0.4-1.0 dB superior to those of its non-adaptive counterpart.",

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AU - Jafarkhani, H.

AU - Farvardin, N.

AU - Lee, C. C.

PY - 1994

Y1 - 1994

N2 - In this paper we present an adaptive discrete wavelet transform image coding scheme. The main contribution of the work is in developing a simple classification procedure which is used to classify the subband blocks into a finite number of classes. The classified subband blocks are subsequently encoded. The low frequency band is encoded by means of a 2-D DCT using entropy-coded trellis coded quantization (ECTCQ); other bands are directly encoded using ECTCQ. The peak signal-to-noise ratio results of the proposed adaptive system are 0.4-1.0 dB superior to those of its non-adaptive counterpart.

AB - In this paper we present an adaptive discrete wavelet transform image coding scheme. The main contribution of the work is in developing a simple classification procedure which is used to classify the subband blocks into a finite number of classes. The classified subband blocks are subsequently encoded. The low frequency band is encoded by means of a 2-D DCT using entropy-coded trellis coded quantization (ECTCQ); other bands are directly encoded using ECTCQ. The peak signal-to-noise ratio results of the proposed adaptive system are 0.4-1.0 dB superior to those of its non-adaptive counterpart.

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UR - https://www.scopus.com/pages/publications/84998992700#tab=citedBy

U2 - 10.1109/ICIP.1994.413830

DO - 10.1109/ICIP.1994.413830

M3 - Conference article

AN - SCOPUS:84998992700

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VL - 3

SP - 343

EP - 347

JO - Proceedings - International Conference on Image Processing, ICIP

JF - Proceedings - International Conference on Image Processing, ICIP

M1 - 413830

T2 - The 1994 1st IEEE International Conference on Image Processing

Y2 - 13 November 1994 through 16 November 1994

ER -

Adaptive image coding based on the discrete wavelet transform

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