计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
20期
157-160
,共4页
刘艳林%马苗%刘艳丽%许红飞
劉豔林%馬苗%劉豔麗%許紅飛
류염림%마묘%류염려%허홍비
图像分割%人工鱼群算法%小波变换%噪声抑制
圖像分割%人工魚群算法%小波變換%譟聲抑製
도상분할%인공어군산법%소파변환%조성억제
image segmentation%Artificial Fish Swarm algorithm(AFSA)%wavelet transform%noise reduction
针对传统的图像分割方法计算量大、抗噪性弱等问题,将新型的智能仿生优化算法--人工鱼群算法(Artificial Fish Swarm Algorithm,AFSA)和小波变换有效地应用到图像分割中,并提出一种并行的阈值分割方法。采用合适的固定步长与自适应步长相结合的方法提高AFSA收敛速度,利用小波变换对小波系数进行阈值处理来提升图像信噪比。利用二维Otsu作为人工鱼群算法的适应度函数,以获得最优阈值。实验结果显示,该方法在分割质量和降噪方面较潘喆等人提出的方法有明显提高。
針對傳統的圖像分割方法計算量大、抗譟性弱等問題,將新型的智能倣生優化算法--人工魚群算法(Artificial Fish Swarm Algorithm,AFSA)和小波變換有效地應用到圖像分割中,併提齣一種併行的閾值分割方法。採用閤適的固定步長與自適應步長相結閤的方法提高AFSA收斂速度,利用小波變換對小波繫數進行閾值處理來提升圖像信譟比。利用二維Otsu作為人工魚群算法的適應度函數,以穫得最優閾值。實驗結果顯示,該方法在分割質量和降譟方麵較潘喆等人提齣的方法有明顯提高。
침대전통적도상분할방법계산량대、항조성약등문제,장신형적지능방생우화산법--인공어군산법(Artificial Fish Swarm Algorithm,AFSA)화소파변환유효지응용도도상분할중,병제출일충병행적역치분할방법。채용합괄적고정보장여자괄응보장상결합적방법제고AFSA수렴속도,이용소파변환대소파계수진행역치처리래제승도상신조비。이용이유Otsu작위인공어군산법적괄응도함수,이획득최우역치。실험결과현시,해방법재분할질량화강조방면교반철등인제출적방법유명현제고。
To solve the problem of large calculation and sensitivity to noise disturbance in image segmentation, this paper com-bines a novel intelligence optimization algorithm, i.e. the artificial fish swarm algorithm, with discrete wavelet transform, and proposes a parallel segmentation method for noise-polluted images. The suggested method employs a special scheme to decide the step of individuals in the fish swarm to improve the speed of convergence, which integrates the fixed step and the adaptive step. On the other hand, discrete wavelet transform is introduced to improve the signal-to-noise ratio of segmented images, in which appropriate wavelet coefficients are selected to reconstruct a noise-suppressed image. The 2D Otsu method serves as the fitness function for the improved AFSA to obtain an optimal threshold. Experimental results show that the proposed method is superior to the method proposed by Pan and Wu in terms of segmenting effect and noise reduction.