TECHNICAL FIELD

The present invention relates generally to imaging and, more particularly, to image noise filtering techniques.

BACKGROUND

In the field of image capture and processing, row and column noise is a recurring problem. In this regard, various components of imaging systems may produce some amount of noise that becomes unintentionally added to captured images. For example, certain circuit components (e.g., row or column amplifiers) may be used during the capture and readout of all pixel data associated with a given column or row. Manufacturing variations or calibration errors associated with such components can therefore affect all pixel data that is captured and read out. This can result in rows or columns of the captured images exhibiting offsets that manifest as horizontal or vertical lines. When this noise varies over time (e.g., temporal noise caused by fluctuations in temperature or other factors), it can result in flickering rows or columns.

Such noise is generally easily perceived by human observers and can therefore significantly degrade a user's experience when the images viewed in video form. However, this noise is often very difficult for machine-based processes to detect and remove in a reliable and computationally efficient manner, as such noise often affects a relatively large portion of an image (e.g., a large spatial area corresponding to an entire row or column). In this regard, it is often difficult for conventional noise reduction processes to effectively discriminate between scene-based information and temporally changing noise.

Moreover, existing noise reduction approaches often require processing of individual pixels or neighborhoods of pixels to identify noise. Unfortunately, such approaches can be extremely computationally intensive and may require realtime processing of thousands or even millions of individual pixel values. As a result, such conventional approaches are usually unsuitable for use in embedded systems where available computational power and memory may be insufficient for such processing.

SUMMARY

Improved techniques for image noise reduction are provided using spectral transforms.

By applying spectral transforms to row and column values associated with captured image frames, basis function components associated with noise may be selectively reduced to provide adjusted row and column values. The adjusted row and column values may be used to generate row and column offset terms to effectively filter out the noise from the captured images in an efficient and effective manner.

In one embodiment, a method includes determining row values for image frames comprising scene information and noise information; performing first spectral transforms in a first domain on corresponding subsets of the row values to determine first spectral coefficients; performing second spectral transforms in a second domain on corresponding subsets of the first spectral coefficients to determine second spectral coefficients; selectively adjusting the second spectral coefficients; and determining row correction terms based on the adjusted second spectral coefficients to reduce the noise information of the image frames.

In another embodiment, a system includes a memory component storing machine-executable instructions; and a processor configured to execute the instructions to cause the system to: determine row values for image frames comprising scene information and noise information, perform first spectral transforms in a first domain on corresponding subsets of the row values to determine first spectral coefficients, perform second spectral transforms in a second domain on corresponding subsets of the first spectral coefficients to determine second spectral coefficients, selectively adjust the second spectral coefficients, and determine row correction terms based on the adjusted second spectral coefficients to reduce the noise information of the image frames.

In another embodiment, a method includes determining a plurality of column mean values for an image frame comprising scene information and noise information; performing a spectral transform on at least a subset of the column mean values to determine spectral coefficients; adjusting the spectral coefficients to reduce the scene information; performing a reverse spectral transform on the adjusted spectral coefficients to determine adjusted column mean values; and generating column correction terms to reduce the noise information using the adjusted column mean values.

In another embodiment, a system includes a memory component storing machine-executable instructions; and a processor configured to execute the instructions to cause the system to: determine a plurality of column mean values for an image frame comprising scene information and noise information, perform a spectral transform on at least a subset of the column mean values to determine spectral coefficients, perform an adjustment of the spectral coefficients to reduce the scene information, perform a reverse spectral transform on the adjusted spectral coefficients to determine adjusted column mean values, and generate column correction terms to reduce the noise information using the adjusted column mean values.

The scope of the invention is defined by the claims, which are incorporated into this section by reference. A more complete understanding of embodiments of the invention will be afforded to those skilled in the art, as well as a realization of additional advantages thereof, by a consideration of the following detailed description of one or more embodiments. Reference will be made to the appended sheets of drawings that will first be described briefly.

