Noise reduction and feature enhancement for a thermal imaging camera
Thermal cameras, particularly less elaborate inexpensive designs, may deliver high temperature resolution at the expense of less clear displayed images. For many low visibility uses, such as firefighting, it may be advantageous to sacrifice some temperature detail for clarity and object recognition. Without sacrificing the actual detailed temperature information available in a captured scene, it may be beneficial to apply filters in series to raw image data that reduce visible noise and build back in feature contrast for the purposes of providing a user a displayed image that permits ease of object recognition, while still providing the raw data to a thermography module to maintain high resolution of temperature information if desired. In addition, more efficient and useful edge highlighting techniques are disclosed. For very low contrast scenes, such as smoky rooms and the like, other specific filters and equalization methods may be applied.
1. A column noise correction filter method for a digital image frame of input pixel values arranged in a series of rows and columns, the method comprising, for each column of the image frame:
dividing pixels of the column into blocks of n pixels;
creating a first measure of central tendency for each block;
grouping each block with m adjacent blocks from adjacent columns;
creating a second measure of central tendency of the first central tendency values for each m block grouping; and
subtracting the second measure of central tendency from the first measure of central tendency to create a column noise correction value which is subtracted from each corresponding input pixel to create a column noise filtered image frame.
2. The column noise correction filter method of claim 1 wherein the row noise correction values is further interpolated between adjacent rows before being applied.
3. The column noise correction filter method of claim 1 wherein the first measure is an average, and the second measure is a median.
4. The column noise correction filter method of claim 1 wherein the blocks are chosen to overlap.
5. The column noise correction filter method of claim 1 wherein n=one of 8 or 16, and m=5.
6. The column noise correction filter method of claim 1 , further comprising determining a contrast of the scene based on a width of a histogram of the image intensity values of at least one of all or a subset of pixels in an image frame of the scene and applying column filter steps to columns if the contrast is below a predetermined value.
7. A row noise correction filter method for a digital image frame of input pixel values, the method comprising, for each row of the image frame:
creating a first measure of central tendency to the row of all the pixels in the row;
dividing the row into blocks of k pixels;
creating a second measure of central tendency of the pixels in each block;
subtracting, for each block, the second measure of central tendency from the first measure of central tendency to create an intermediate correction factor;
creating a third measure based on the intermediate correction factors;
creating a row noise correction factor comprising a difference between the intermediate product and the third measure; and
subtracting the row noise correction value from each corresponding input pixels to create a row noise filtered image.
8. The row noise correction filter method of claim 7 wherein the first measure is mean, the second measure is median, and the third measure is mean.
9. The row noise correction filter method of claim 7 wherein k=7.
10. The row noise correction filter method of claim 7 , further comprising determining a contrast of the scene based on a width of a histogram of the image intensity values of at least one of all or a subset of pixels in an image frame of the scene and applying row filter steps to columns if the contrast is below a predetermined value.
11. A method for highlighting edge features in a thermal image in a thermal camera including a thermal imaging sensor, and image processing capability for implementing a signal processing chain of processor executed functions, the method comprising;
receiving image frame data at a colorization element and an edge highlighting filter element in the signal processing chain, the image data comprising frames of pixel values;
assigning colors to each pixel corresponding to a predetermined relationship between color and at least one of pixel intensity or scene temperature of the region of the imaged scene corresponding to a given pixel, wherein the colors are assigned from a primary color look up table (LUT);
applying an edge filter to the frame pixels to generate a map of edge strength values of each pixel;
converting the edge strength values to a histogram of discrete edge strength bins comprising a number of edge strength bins corresponding to pixel edge strength above a predetermined value divided into a predetermined number of bins;
creating a series of color LUTs each color LUT in the series comprising a shift in brightness from the primary color LUT, wherein the number of color LUTs corresponds to the predetermined number of bins, and the shift in brightness between each color LUT corresponds to a total desired shift for maximum edge strength divided by the predetermined number of bins; and
replacing the colors assigned to individual pixels from the primary color LUT that have a pixel edge strength above the predetermined value, with colors from the shifted LUT corresponding to the individual pixel's edge strength bin.