CAJ | 학술논문

自动对焦技术对于数字相机至关重要，它是获取清晰图像的重要手段。针对复杂环境下多目标场景图像，提出了一种基于光流场估计的自动对焦算法。通过计算输入图像序列的光流场，对场景中的运动目标进行检测，根据目标运动属性准确判断出感兴趣目标。改进了Brenner清晰度评价方法，利用目标的二维边缘梯度信息建立评价函数，并且通过非线性增益提高评价函数的灵敏度，减小了噪声对评价值的影响。实验证明，该算法能够在主辅目标景深比达50倍的情况下分辨出感兴趣主目标，并在方差为0.02的随机噪声干扰下能有效地评价图像的清晰度；此算法将Brenner等评价函数的峰值稳定余量提高了1至4倍，对于不同图像具有良好的鲁棒性，易于硬件实现。
자동대초기술대우수자상궤지관중요，타시획취청석도상적중요수단。침대복잡배경하다목표장경도상，제출료일충기우광류장고계적자동대초산법。통과계산수입도상서렬적광류장，대장경중적운동목표진행검측，근거목표운동속성준학판단출감흥취목표。개진료Brenner청석도평개방법，이용목표적이유변연제도신식건립평개함수，병차통과비선성증익제고평개함수적령민도，감소료조성대평개치적영향。실험증명，해산법능구재주보목표경심비체50배적정황하분변출감흥취주목표，병재방차위0.02적수궤조성간우하능유효지평개도상적청석도；차산법장Brenner등평개함수적봉치은정여량제고료1지4배，대우불동도상구유량호적로봉성，역우경건실현。
Auto-Focus technique is a main approach to hunt clear images which plays an important role in digital camera application. According to several unknown target under complicated condition, a novel auto-focus algorithm was proposed based on optical flow estimation. By calculating the optical flow of each input frame, the moving targets in scene image were tested as well as according to the moving characteristic, the interested real target was judged. Brenner sharpness evaluation method was improved. Meanwhile the evaluation function was established using two dimensions edge-gradient information. The response sensitivity of evaluation function was also increased via nonlinear-gain coefficient the impact of noise on evaluation value was decreased. Experimental results show that the proposed method can distinguish the interested main target in 50 times depths of field of different targets and evaluate the definition of varied images with random noise in 0.02 variance value effectively. And it is of a good ability of robustness for different images, Brenner function improves the peak stability margin 1 to 4 times by the algorithm, and it can be easily achieved on hardware.