TECHNIQUES FOR CONVOLUTIONAL NEURAL NETWORK-BASED MULTI-EXPOSURE FUSION OF MULTIPLE IMAGE FRAMES AND FOR DEBLURRING MULTIPLE IMAGE FRAMES

• Main Authors: GLOTZBACH JOHN W, PEKKUCUKSEN IBRAHIM, HU YUTING, ZHEN RUIWEN, SHEIKH HAMID R
• Format: Patent
• Language: Chinese; English
• Published: 28.09.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC COMMUNICATION TECHNIQUE; ELECTRICITY; PHYSICS; PICTORIAL COMMUNICATION, e.g. TELEVISION

A method includes the steps of: obtaining multiple image frames of a scene using at least one camera of an electronic device. The method also includes using a convolutional neural network to generate blending maps associated with the image frames. The blending maps contain or are based on both a measure of motion in the image frames and a measure of how well exposed different portions of the image frames are. The method further includes generating a final image of the scene using at least some of the image frames and at least some of the blending maps. The final image of the scene may be generated by blending the at least some of the image frames using the at least some of the blending maps, and the final image of the scene may include image details that are lost in at least one of the image frames due to over-exposure or under-exposure. 一种方法包括使用电子装置的至少一个相机获得场景的多个图像帧。该方法也包括使用卷积神经网络来生成与图像帧相关联的混合图。混合图包含或基于图像帧中的运动测量值和图像帧的不同部分的曝光程度如何的测量值两者。该方法还包括使用图像帧中的至少一些和混合图中的至少一些来生成场景的最终图像。可通过使用混合图中的至少一些来混合图像帧中的至少一些，生成场景的最终图像