GPGPU based Depth Image Enhancement Algorithm

Cuckoo Optimization Algorithm based Image Enhancement

This paper proposes an extension to approach proposed in [13] for image enhancement using a combination of fuzzy logic technique and bio-inspired optimization algorithm. The transformation of the image data from RGB to HSV space has been done without altering HUE information. The image has been categorized into three regions with well tuned membership functions: underexposed, overexposed and mi...

GPGPU Acceleration of the KAZE Image Feature Extraction Algorithm

The recently proposed open-source KAZE image feature detection and description algorithm [1] offers unprecedented performance in comparison to conventional ones like SIFT and SURF as it relies on nonlinear scale spaces instead of Gaussian linear scale spaces. The improved performance, however, comes with a significant computational cost limiting its use for many applications. We report a GPGPU ...

Guided Filters for Depth Image Enhancement

Persian sign language detection based on normalized depth image information

There are many reports of using the Kinect to detect hand and finger gestures after release of device by Microsoft. The depth information is mostly used to separate the hand image in the two-dimension of RGB domain. This paper proposes a method in which the depth information plays a more dominant role. Using a threshold in depth space first the hand template is extracted. Then in 3D domain the ...

Speed up a Machine-Learning-based Image Super-Resolution Algorithm on GPGPU

We develop a CUDA program to recover the 3x super-resolution version of a given low-resolution grayscale image using a machine-learning-based method. We discuss the implementation of the program, and show that it can produce high-quality super-resolution images and achieve high performance on GPU. We also point out the limitations and potential improvements of the program.