计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
19期
180-185
,共6页
CV模型%目标提取%NSCT方法%图像融合
CV模型%目標提取%NSCT方法%圖像融閤
CV모형%목표제취%NSCT방법%도상융합
CV model%target extraction%NSCT method%image fusion
针对传统融合方法在光照不足、目标隐藏或目标和背景颜色接近时,容易出现目标信息丢失或减弱的现象,提出一种将基于CV模型的目标提取与NSCT相结合的方法。该方法使用动态轮廓线模型对红外目标进行搜索检测识别,将源图像序列分为目标和背景区域,利用非下采样Contourlet变换对输入图像进行多尺度、多方向稀疏分解,准确捕获图像中的高维奇异信息,并在目标和背景区域里分别采用不同的融合规则,将其与小波融合方法、拉普拉斯融合方法、NSCT方法作对比,并通过熵、平均梯度、空间频率、标准差等参数对融合后的图像进行定量分析。实验结果表明,该方法不但较好地提高了融合图像的目标探测性,而且融合结果中的目标比较清晰,亮度较高,目视效果较好,在主观视觉效果与客观评价指标上均取得了很好的融合效果。
針對傳統融閤方法在光照不足、目標隱藏或目標和揹景顏色接近時,容易齣現目標信息丟失或減弱的現象,提齣一種將基于CV模型的目標提取與NSCT相結閤的方法。該方法使用動態輪廓線模型對紅外目標進行搜索檢測識彆,將源圖像序列分為目標和揹景區域,利用非下採樣Contourlet變換對輸入圖像進行多呎度、多方嚮稀疏分解,準確捕穫圖像中的高維奇異信息,併在目標和揹景區域裏分彆採用不同的融閤規則,將其與小波融閤方法、拉普拉斯融閤方法、NSCT方法作對比,併通過熵、平均梯度、空間頻率、標準差等參數對融閤後的圖像進行定量分析。實驗結果錶明,該方法不但較好地提高瞭融閤圖像的目標探測性,而且融閤結果中的目標比較清晰,亮度較高,目視效果較好,在主觀視覺效果與客觀評價指標上均取得瞭很好的融閤效果。
침대전통융합방법재광조불족、목표은장혹목표화배경안색접근시,용역출현목표신식주실혹감약적현상,제출일충장기우CV모형적목표제취여NSCT상결합적방법。해방법사용동태륜곽선모형대홍외목표진행수색검측식별,장원도상서렬분위목표화배경구역,이용비하채양Contourlet변환대수입도상진행다척도、다방향희소분해,준학포획도상중적고유기이신식,병재목표화배경구역리분별채용불동적융합규칙,장기여소파융합방법、랍보랍사융합방법、NSCT방법작대비,병통과적、평균제도、공간빈솔、표준차등삼수대융합후적도상진행정량분석。실험결과표명,해방법불단교호지제고료융합도상적목표탐측성,이차융합결과중적목표비교청석,량도교고,목시효과교호,재주관시각효과여객관평개지표상균취득료흔호적융합효과。
In order to solve the problem that the target information is easily lost or impaired when the target is hided or the color of target is close to the background or lack of light, a new method that combined NSCT and target extraction based on CV model is proposed. The method uses the dynamic contour model to search, test and identify the infrared target, then divides the source image sequence into target and background region, and uses non-subsampled Contourlet transform to sparse decomposition in multi-scale and multi-directions for getting high-dimensional singular information accurately. Different fusion rules are used in target and background region respectively, and this method is compared with wavelet fusion method, Laplace fusion method, and NSCT fusion method. Quantitative analysis is carried out for the fused image under parameters like entropy, average gradi-ent, spatial frequency and standard deviation. The results show that this method can not only make the detection of fusion target more easily, but also make the target look clear and brighter. A good fusion effect in subjective visual andobjective evaluation index is obtained.