Parallel Computation for Discrete Orthogonal Moments of Images Using Graphic Processing Unit
A novel method is proposed for fast computing discrete orthogonal
moments of large scale digital images using CUDA (Compute Unified Device
Architecture) on GPU (Graphic Processing Unit). After original input
image loading and mapping by partition model, parallelism was
implemented by dividing onto GPU. Experimental results show that the
proposed method outperforms the existing software implementation
approaches, such as direct method, recursive algorithm based on CPU and
so on, especially for larger images and higher order moments which can
be performed in real-time.