Method and system of correcting defective pixels

#The subject matter herein generally relates to image process technologies, and particularly to a method and a system of correcting defective pixels of a digital image.

#Digital cameras generally adapt a Charge-Coupled Device (CCD) or Complementary Metal Oxide Semiconductor (CMOS) as a sensor. These sensors may have some defective pixels, including bright pixels and dark pixels, attributed to production issues. These defective pixels are pixels having an abnormal photosensitivity, and are not controllable by the photosensitive system. The dark pixels cannot sense lights, and the bright pixels always output high intensify values. If the pixel values of these defective pixels are not compensated for, image quality would be affected by pixels that should not have existed in the captured scene in the photo. In testing the digital cameras at the factory or self-testing, the coordinates of these defective pixels are measured and recorded, and are stored in a Random Access Memory (RAM) or Read Only Memory (ROM) for storing detect correction data. In actual shooting of images, the digital camera will correct the pixel value of the defective pixel in real time to compensate for the defective pixel usually by calculating a corrected pixel value of the defective pixel based on the pixel values of pixels in the neighborhood of the defective pixel.

#Since neighboring pixels generally have similar pixel values to the defective pixel an average pixel value of the pixel surrounding the defective pixel is generally used as the corrected pixel value of she defective pixel. Referring to FIG. 1, a typical RGB Bayer sensor uses an average pixel value of the neighboring pixels of the defective pixel in a given color channel as the corrected pixel value of the defective pixel. Take R channel as an example. The position of a defective pixel R22 has been marked, and an average pixel value of eight pixels nearest to the defective pixel R22 is calculated as the corrected pixel value {circumflex over (R)}22:

#Implementations of the present technology will now be described, by way of example only, with reference to the attached figures, wherein:

#FIG. 1 is a diagram illustrating a conventional method of correcting defective pixels;

#FIG. 2 is a diagram illustrating the correction of pixels by the conventional method of FIG. 1;

#Referring to FIG. 3, a flowchart illustrating a method of correcting defective pixels according to an embodiment of the present disclosure. The method includes the following steps:

#In step S10, each defective pixel is pre-corrected.

#If there are other defective pixels neighboring a specific defective pixel, the pixel value of the specific defective pixel cannot be corrected. Therefore, each defective pixel is first pre-corrected. In step S10, a set of pixel representing positions of defective pixels ascertained at the factory or by the user is defines as Cp: {P1, P2, . . . , PI}. The set of pixels Cp is traversed. That is, for each defective pixel Pi, 1≤i≤I, in Cp, a pre-corrected pixel value is adopted as the pixel value of each defective pixel Pi by pre-correcting set Cp using the conventional averaging method. It is understood that, in other embodiments, a defective pixel can also be pre-corrected using a nearest neighbor method, i.e., using a pixel value of the surrounding normal pixels as the pixel value of the defective pixel.