Optimization of a single seam removal using a GPU
نویسندگان
چکیده
In this paper we consider the problem of implementing and optimizing the Seam Carving algorithm on graphics processing units. Seam Carving is a content-aware image resizing method proposed by Avidan and Shamir. In order to use their proposed method in real-time application, a pre-processing step is needed. While some other papers propose real-time resizing by changing the original Seam Carving method, this paper focuses on optimizing the basic single-seam method, for use on CUDA GPUs. To our best knowledge none has focused on optimizing this single-seam method so that it would best fit the GPU architecture.
منابع مشابه
Fast Cellular Automata Implementation on Graphic Processor Unit (GPU) for Salt and Pepper Noise Removal
Noise removal operation is commonly applied as pre-processing step before subsequent image processing tasks due to the occurrence of noise during acquisition or transmission process. A common problem in imaging systems by using CMOS or CCD sensors is appearance of the salt and pepper noise. This paper presents Cellular Automata (CA) framework for noise removal of distorted image by the salt an...
متن کاملParallel Implementation of Particle Swarm Optimization Variants Using Graphics Processing Unit Platform
There are different variants of Particle Swarm Optimization (PSO) algorithm such as Adaptive Particle Swarm Optimization (APSO) and Particle Swarm Optimization with an Aging Leader and Challengers (ALC-PSO). These algorithms improve the performance of PSO in terms of finding the best solution and accelerating the convergence speed. However, these algorithms are computationally intensive. The go...
متن کاملAn approach to Improve Particle Swarm Optimization Algorithm Using CUDA
The time consumption in solving computationally heavy problems has always been a concern for computer programmers. Due to simplicity of its implementation, the PSO (Particle Swarm Optimization) is a suitable meta-heuristic algorithm for solving computationally heavy problems. However, despite the simplicity, the algorithm is inefficient for solving real computationally heavy problems but the pr...
متن کاملParallelization of Rich Models for Steganalysis of Digital Images using a CUDA-based Approach
There are several different methods to make an efficient strategy for steganalysis of digital images. A very powerful method in this area is rich model consisting of a large number of diverse sub-models in both spatial and transform domain that should be utilized. However, the extraction of a various types of features from an image is so time consuming in some steps, especially for training pha...
متن کاملAccelerating high-order WENO schemes using two heterogeneous GPUs
A double-GPU code is developed to accelerate WENO schemes. The test problem is a compressible viscous flow. The convective terms are discretized using third- to ninth-order WENO schemes and the viscous terms are discretized by the standard fourth-order central scheme. The code written in CUDA programming language is developed by modifying a single-GPU code. The OpenMP library is used for parall...
متن کامل