In the area of computational imaging, we aim to improve synthetic images by leveraging
advanced algorithms and computational techniques. Our innovative approaches enhance
generated images quality, enables new functionalities, and pushes the boundaries of what
conventional image-generation can achieve.
a. Composite Image Synthesis
In this study, our focus is on refining image composition techniques, widely
employed in the television and film industry for creating seamless synthetic visual
effects. The goal is to develop methods that adeptly capture global effects linked
with specific local content from one image and seamlessly integrate them into a
second image.
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b. Image Morphing
In this study, we focus on exploring image morphing techniques. We aim to
facilitate the transformation from a source image to a target image by developing
methods that seamlessly blend features, providing a comprehensive understanding
of the morphing process.
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c. Multi Focus Image Fusion
Multi-focus image fusion is a crucial research area within information fusion
field. The primary goal is to extend the depth of field by extracting focused
regions from multiple partially focused images and integrating them into a
composite image where all objects achieve clarity. We develop multi-focus image
fusion algorithms that employ Content Adaptive Blurring (CAB) and other
techniques to detect and merge these focused regions.
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d. Image Inpainting
In this study, our focus revolves around the imperative task of detecting and
removing unwanted structures from digital images, particularly when essential
parts of the scene become occluded by such elements. The challenge lies in the
tedious and time-consuming nature of manually marking the boundaries of these
unwanted structures. To address this, we introduce novel algorithms designed to
efficiently detect and remove unwanted structures with minimal user input.
Related Publications
● Image de-fencing framework with hybrid inpainting algorithm, Signal, Image and Video Processing (SIVP), 2016
● Image inpainting using cubic hermit spline, International Conference on Graphic and Image Processing (ICGIP), 2011
● Image inpainting based on pyramids, IEEE 10th International Conference on Signal Processing (ICSP), 2010