Open AccessLow‐complexity and efficient image coder/decoder with quad‐tree search model for embedded computing platforms
Author(s) -
Ma Tao
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0469
Subject(s) - set partitioning in hierarchical trees , codec , computer science , image compression , computational complexity theory , decoding methods , variable length code , algorithm , coding (social sciences) , tree structure , theoretical computer science , image processing , image (mathematics) , artificial intelligence , mathematics , computer hardware , binary tree , statistics
Among the existing image coding methods, set partition in hierarchy tree (SPIHT) becomes a favourable choice for the energy‐constrained embedded computing system because of its simplicity and high coding efficiency. In this study, the authors presented a quad‐tree search model which is able to provide the higher coding efficiency than the model used in SPIHT. By applying this model, the authors proposed a new image codec, which is able to surpass SPIHT by 0.2–0.5 dB in peak signal‐to‐noise ratio over various code rates, and its performance is even comparable to SPIHT with adaptive arithmetic code and JPEG2000. Also an experiment is conducted to show the complexity of the proposed codec is the same as SPIHT without the complicated arithmetic codes. This property is critically favoured in embedded processing communication systems where energy consumption and speed are priority concerns.