Method and computer system of white point detection
A method of white point detection for an image is disclosed. The method includes determining a plurality of pixels of the image as a plurality of white point candidates; estimating a plurality of candidate confidences according to a plurality of brightness values corresponding to the plurality of white point candidates; and determining a plurality of white points of the image according to the plurality of candidate confidences.
1. A method of white point detection for an image, comprising:
determining a plurality of pixels of the image as a plurality of white point candidates;
estimating a plurality of candidate confidences according to a plurality of brightness values corresponding to the plurality of white point candidates; and
determining a plurality of white points of the image according to the plurality of candidate confidences;
wherein the image includes a plurality of regions, and each of the plurality of regions includes at least one pixel having a largest channel value;
wherein the step of estimating the plurality of candidate confidences according to the plurality of brightness values corresponding to the plurality of white point candidates comprises:
finding a maximal brightness value of the plurality of brightness values nearby each of the plurality of white point candidates; and
converting the maximal brightness value of the white point candidate to the candidate confidence.
2. The method of claim 1 , wherein each of the plurality of white points has a largest channel value in a range, and the each of the plurality of white points is a center of the range.
3. The method of claim 2 , wherein the range is a circle or a square, and a size of the range is related to the image.
4. The method of claim 2 , wherein the center is a centroid or an in-center of the range.
5. The method of claim 1 , wherein the step of determining the plurality of white points of the image according to the plurality of candidate confidences comprises:
rejecting candidate confidences corresponding to white point candidates of low confidence from the plurality of candidate confidences; and
determining remaining candidate confidences within the plurality of candidate confidences as the plurality of white points of the image.
6. A computer system capable of performing white point detection in an image, comprising:
a processing device; and
a memory device coupled to the processing device, for storing a program code instructing the processing device to perform a process, wherein the process comprises:
determining a plurality of pixels of the image as a plurality of white point candidates;
estimating a plurality of candidate confidences according to a plurality of brightness values corresponding to the plurality of white point candidates; and
determining a plurality of white points of the image according to the plurality of candidate confidences;
wherein the image includes a plurality of regions, and each of the plurality of regions includes at least one pixel having a largest channel value;
wherein the step of estimating the plurality of candidate confidences according to the plurality of brightness values corresponding to the plurality of white point candidates comprises:
finding a maximal brightness value of the plurality of brightness values nearby each of the plurality of white point candidates; and
converting the maximal brightness value of the white point candidate to the candidate confidence.
7. The computer system of claim 6 , wherein each of the plurality of white points has a largest channel value in a range, and the each of the plurality of white points is a center of the range.
8. The computer system of claim 7 , wherein the range is a circle or a square, and a size of the range is related to the image.
9. The computer system of claim 7 , wherein the center is a centroid or an in-center of the range.
10. The computer system of claim 6 , wherein the step of determining the plurality of white points of the image according to the plurality of candidate confidences comprises:
rejecting candidate confidences corresponding to white point candidates of low confidence from the plurality of candidate confidences; and
determining remaining candidate confidences within the plurality of candidate confidences as the plurality of white points of the image.