Image compression using a new discrete multiwavelet transform and a new embedded vector quantization

Embedded quantization is a mechanism through which image coding systems provide quality progressivity. Although the most common embedded quantization approach is to use uniform scalar deadzone quantization (USDQ) together with bitplane coding (BPC), recent work suggested that similar coding performance as that achieved with USDQ+BPC can be obtained with a general embedded quantization (GEQ) scheme than performs fewer quantization stages. Unfortunately, practical approaches of GEQ can not be implemented in bitplane coding engines without substantially modifying their structure. This work overcomes this drawback introducing a 2-step scalar deadzone quantization (2SDQ) scheme compatible with bitplane image coding that provides the same advantages of practical GEQ approaches. Herein, 2SDQ is introduced in the framework of JPEG2000 to demonstrate its viability and efficiency.

show abstract

Cell-Based 2-Step Scalar Deadzone Quantization for JPEG2000

Bartrina-Rapesta

Aulí-Llinàs

Serra-Sagristà

2014

2014 Data Compression Conference

View full text Add to dashboard Cite

Image compression using a new discrete multiwavelet transform and a new embedded vector quantization

Cited by 17 publications

References 24 publications

Fine granularity scalable speech coding using embedded tree-structured vector quantization

Fine granularity scalable speech coding using embedded tree-structured vector quantization

Low Complexity Embedded Quantization Scheme Compatible with Bitplane Image Coding

Cell-Based 2-Step Scalar Deadzone Quantization for JPEG2000

Contact Info

Product

Resources

About