Eueung Mulyana
Papers
1
Total Citations
4
H-Index
1
About
Eueung Mulyana is a researcher whose work bridges image processing, sensor technology, and quality assessment. His key research areas include image quality assessment, region-of-interest (ROI) analysis, and the application of depth sensors like the Kinect. One of his notable contributions is the development of a "ROI Based Post Image Quality Assessment Technique on Multiple Localized Filtering Method on Kinect Sensor," which introduces a targeted approach to evaluating image quality by focusing on specific regions rather than the entire frame. This method leverages the Structural Similarity Index (SSI) to produce a quantitative assessment, with output values ranging from 1 (identical) to -1 (completely dissimilar). Although his most-cited paper has garnered 4 citations, the work demonstrates a practical application of localized filtering and sensor data processing, contributing to advancements in real-time image evaluation. Mulyana’s research is particularly relevant for fields such as computer vision, human-computer interaction, and automated quality control, where precise and efficient image assessment is critical. His focus on ROI-based techniques offers a nuanced alternative to traditional full-image metrics, highlighting his commitment to improving the accuracy and relevance of image quality models in sensor-driven environments.
Research Focus
Key Achievements
Top Papers
- 1