عنوان البحث(Papers / Research Title)
Removing Spatial Redundancy from Image by Using Variable Vertex Chain Code
الناشر \ المحرر \ الكاتب (Author / Editor / Publisher)
توفيق عبد الخالق عباس الاسدي
Citation Information
توفيق,عبد,الخالق,عباس,الاسدي ,Removing Spatial Redundancy from Image by Using Variable Vertex Chain Code , Time 17/06/2014 06:40:57 : كلية تكنولوجيا المعلومات
وصف الابستركت (Abstract)
Removing Spatial Redundancy from Image by Using Variable Vertex Chain Code
الوصف الكامل (Full Abstract)
Removing Spatial Redundancy from Image by Using Variable Vertex Chain Code
TAWFIQ A. AL-ASADI
College of Information Technology
Babylon University
Iraq
FANAR ALI JODA
College of Information Technology
Babylon University
Iraq
Abstract:-
In this paper we have proposed an efficient lossless image compression method, this method consists of two parts, the first is compressed part that based on two approaches of chain code representation the first approach is variable vertex chain code (V_VCC) is used to encode boundary of segment to remove spatial redundancy in image, the second approach is Freeman chain code 8-directional (FCCE) is used to encode remaining values then the values that belong to two approaches of chain code will be removed from image and reduce the size of image then begins a new level and will apply the same steps as the previous, the second is decompressed part , depending on variable vertex chain code set, Freeman chain code set, start points and values decompressed part will rebuild the original image identically.
Key words: Chain code, Lossless image compression, FCCE, Segmentation, V_VCC.
1. Introduction
Computer imaging plays an important role in many areas
Tawfiq A. Al-Asadi,
Fanar Ali Joda- Removing Spatial Redundancy from Image by
Using Variable Vertex Chain Code
EUROPEAN ACADEMIC RESEARCH - Vol. II, Issue 1 / April 2014
ranging from consumer digital photo albums to remote earth sensing. The growing production of images and demands to their quality require high performance compression systems for efficient transmission, storage and archival (Krivoulets 2004).Various types of redundancy exist in images, such as temporal redundancy, spatial redundancy (or interpixel redundancy), coding redundancy, spectral redundancy and psychovisual redundancy. The main goal of image compression is to minimize the number of bits required to represent the original images by reducing the redundancy in images, the essential issue in image compression is to design efficient and effective compression schemes (Zha 2007).
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