Abstract: A method and an apparatus for designing an image restoration filter and a method and an apparatus for restoring an image by using the image restoration filter are provided. A test image is captured by an imaging system to obtain image information of the test image. The image restoration filter is then calculated according to original image information of the test image and the image information obtained by the imaging system through a numerical method, such that the obtained image information after being processed by the image restoration filter has a better similarity to the original image information. Thereafter, an image captured by the imaging system is processed by using the image restoration filter as a kernel, so as to resolve the problems of image blur and distortion caused by the optical path and the imaging system.

Abstract: An apparatus for evaluating a volume of an object and a method thereof are provided. The provided apparatus and the method can precisely evaluate the volume of the object with a single camera, and the required evaluation time is short. Accordingly, shipping companies can utilize the most appropriate container or cargo space for each object to deliver, thereby reducing operation costs and optimizing the transportation fleet.

Abstract: A distance evaluation method for evaluating distances from an observation point to objects within an arbitrary detectable range in a scene is disclosed. The method includes the following steps. First, a focus distance is set to correspond to a lower or higher limit of a chosen detection range. Next, an image is then captured with an image acquisition system, wherein transfer function of the image acquisition system depends on the focus distance. The captured image of the scene is segmented. A blur metric is computed for each image segment of the captured image. The blur metric is associated with the distance of the objects from the observation point in each image segment.

Abstract: A method and a system for developing a new-view image from an original image with a corresponding depth map is provided. The original image has a plurality of original pixels and the new-view image has at least a new-view pixel. The method for developing the new-view image comprises the following steps. According to a corresponding depth value of each original pixel, a corresponding position of each original pixel corresponding to the new-view pixel is estimated. An occupancy proportion of each original pixel occupying the new-view pixel is estimated according to the corresponding position of each original pixel. An estimated color of an estimated partial pixel of the new-view pixel is initially obtained according to the occupancy proportion of one selected original pixel. The estimated partial pixel is updated according to the occupancy proportions and estimated occlusion proportion of the other selected original pixels one by one.

Abstract: A distance evaluation method for evaluating distances from an observation point to objects within an arbitrary detectable range in a scene is disclosed. The method includes the following steps. First, a focus distance is set to correspond to a lower or higher limit of a chosen detection range. Next, an image is then captured with an image acquisition system, wherein transfer function of the image acquisition system depends on the focus distance. The captured image of the scene is segmented. A blur metric is computed for each image segment of the captured image. The blur metric is associated with the distance of the objects from the observation point in each image segment.

Abstract: A method and a system for developing a new-view image from an original image with a corresponding depth map is provided. The original image has a plurality of original pixels and the new-view image has at least a new-view pixel. The method for developing the new-view image comprises the following steps. According to a corresponding depth value of each original pixel, a corresponding position of each original pixel corresponding to the new-view pixel is estimated. An occupancy proportion of each original pixel occupying the new-view pixel is estimated according to the corresponding position of each original pixel. An estimated color of an estimated partial pixel of the new-view pixel is initially obtained according to the occupancy proportion of one selected original pixel. The estimated partial pixel is updated according to the occupancy proportions and estimated occlusion proportion of the other selected original pixels one by one.

Abstract: A method and a system for rendering a multi-view image are provided. The method for rendering the multi-view image includes the following steps. An image capturing unit provides an original image and depth information thereof. Multiple threads of one processing unit perform a pixel rendering process and a hole filling process on at least one row of pixels of the original image according to the depth information by way of parallel processing to render at least one new-view image. View-angles of the at least one new-view image and the original image are different. Each of the threads performs a view interlacing process on at least one pixel of the original image and the at least one new-view image by way of parallel processing to render the multi-view image.

Abstract: An image restoration method is disclosed. The method is used in an image restoration apparatus and configured to restore an image captured by an imaging system. The method includes capturing a scenery image by the imaging system and applying restoration processing to the scenery image using a plurality of restoration filters respectively corresponding to a plurality of depths, to generate a plurality of restored images respectively corresponding to the depths.

Abstract: A method and an apparatus for designing an image restoration filter and a method and an apparatus for restoring an image by using the image restoration filter are provided. A test image is captured by an imaging system to obtain image information of the test image. The image restoration filter is then calculated according to original image information of the test image and the image information obtained by the imaging system through a numerical method, such that the obtained image information after being processed by the image restoration filter has a better similarity to the original image information. Thereafter, an image captured by the imaging system is processed by using the image restoration filter as a kernel, so as to resolve the problems of image blur and distortion caused by the optical path and the imaging system.