Abstract:
An image generation method includes: determining at least one first image capture setting and at least one second image capture setting; controlling an image capture device to generate a plurality of first successive captured images for a capture trigger event according to the at least one first image capture setting and generate a plurality of second successive captured images for the same capture trigger event according to the at least one second image capture setting. Variation of the at least one first image capture setting is constrained within a first predetermined range during generation of the first successive captured images. Difference between the at least one first image capture setting and the at least one second image capture setting is beyond the first predetermined range. Variation of the at least one second image capture setting is constrained within a second predetermined range during generation of the second successive captured images.
Abstract:
One video coding method includes at least the following steps: utilizing a visual quality evaluation module for evaluating visual quality based on data involved in a coding loop; and referring to at least the evaluated visual quality for performing sample adaptive offset (SAO) filtering. Another video coding method includes at least the following steps: utilizing a visual quality evaluation module for evaluating visual quality based on data involved in a coding loop; and referring to at least the evaluated visual quality for deciding a target coding parameter associated with sample adaptive offset (SAO) filtering.
Abstract:
An exemplary video recording method of recording an output video sequence for an image capture module includes at least the following steps: deriving a first video sequence from an input video sequence generated by the image capture module, wherein the first video sequence is composed of a plurality of video frames; calculating an image quality metric value for each of the video frames of the first video sequence; referring to the image quality metric value to select or drop each of the video frames of the first video sequence, and accordingly obtaining a second video sequence composed of selected video frames; and generating the recorded output video sequence according to the second video sequence.
Abstract:
One image processing method has at least the following steps: receiving an image input in a device, wherein the image input is composed of at least one source image; receiving image selection information; regarding a source image included in the image input, checking the image selection information to determine whether the source image is selected or skipped; and performing an object oriented image processing operation upon each selected source image. Another image processing method has at least the following steps: receiving an image input in a device, wherein the image input is composed of at least one source image; receiving algorithm selection information; and regarding a source image included in the image input, checking the algorithm selection information to determine a selected image processing algorithm from a plurality of different image processing algorithms, and performing an image processing operation upon the source image based on the selected image processing algorithm.
Abstract:
A method for performing multi-camera capturing control of an electronic device and an associated apparatus are provided, where the method can be applied to the electronic device. The method may include the steps of: obtaining a plurality of preview images, wherein the plurality of preview images are generated by using at least one lens module of the electronic device; generating at least one distance-related index according to characteristics of the plurality of preview images; and according to the aforementioned at least one distance-related index, selectively controlling whether to allow multi-camera capturing or controlling whether to output warning information. For example, when it is detected that a specific distance-related index within the aforementioned at least one distance-related index falls within a predetermined range, a notification which indicates that a multi-camera capturing function of the electronic device is allowed to be triggered may be output, in order to guarantee the overall performance.
Abstract:
A method for performing multi-camera capturing control of an electronic device and an associated apparatus are provided, where the method can be applied to the electronic device. The method may include the steps of: obtaining a plurality of preview images, wherein the plurality of preview images are generated by using at least one lens module of the electronic device; generating at least one distance-related index according to characteristics of the plurality of preview images; and according to the aforementioned at least one distance-related index, selectively controlling whether to allow multi-camera capturing or controlling whether to output warning information. For example, when it is detected that a specific distance-related index within the aforementioned at least one distance-related index falls within a predetermined range, a notification which indicates that a multi-camera capturing function of the electronic device is allowed to be triggered may be output, in order to guarantee the overall performance.
Abstract:
A method for denoising images by block-matching three-dimensional (BM3D) method is disclosed in the present invention. Embodiments of the present invention are used to improve the quality of captured images. Instead of using the same noise variance to denoise all patches of an image, each patch is processed based on a particular assessed noise variance. The assessed noise variance of one reference patch is determined based on noise variance associated with the patch set or based on content characteristics associated with the patch set. The patch set is obtained by block-matching to find similar patches of the reference patch. Noise reduction in frequency domain is applied to the patch set according to the assessed noise variance of the reference patch. The determining of the assessed noise variance can be performed in spatial domain or in frequency domain.
Abstract:
One image processing method has at least the following steps: receiving an image input in a device, wherein the image input is composed of at least one source image; receiving image selection information; regarding a source image included in the image input, checking the image selection information to determine whether the source image is selected or skipped; and performing an object oriented image processing operation upon each selected source image. Another image processing method has at least the following steps: receiving an image input in a device, wherein the image input is composed of at least one source image; receiving algorithm selection information; and regarding a source image included in the image input, checking the algorithm selection information to determine a selected image processing algorithm from a plurality of different image processing algorithms, and performing an image processing operation upon the source image based on the selected image processing algorithm.
Abstract:
One video coding method includes at least the following steps: utilizing a visual quality evaluation module for evaluating visual quality based on data involved in a coding loop; and referring to at least the evaluated visual quality for performing motion estimation. Another video coding method includes at least the following steps: utilizing a visual quality evaluation module for evaluating visual quality based on data involved in a coding loop; and referring to at least the evaluated visual quality for deciding a target coding parameter associated with motion estimation.
Abstract:
An image resizing method includes at least the following steps: receiving at least one input image; performing an image content analysis upon at least one image selected from the at least one input image to obtain an image content analysis result; and creating a target image with a target image resolution by scaling the at least one input image according to the image content analysis result, wherein the target image resolution is different from an image resolution of the at least one input image.