8.14 Exploring high dynamic range imaging: §5.2 wavelets and hdr

After implementing numerous tone operators, we were curious as to whether or not there were any applications forwavelets in HDR. After researching, we found that while wavelets are more often used for data compression and noise reduction inHDR, wavelets can also be used to create an unsharp mask to adjust the sharpness of an image.

The unsharp mask works by increasing the contrast at the edges. In photography, unsharp masks are created bymaking a blurred version of the original image in a wet darkroom and then overlays the two images. In most cases, the blurredversion is created by applying a Gaussian blur to a copy of the image. The two matrices are then subtracted. If the value in thedifference matrix is greater than a specified threshold, the darker colors are made darker and the lighter colors are made lighter inthe sharpened image.

In our unsharp mask, instead of using a Gaussian blur, we use wavelets to generate the blurred mask. Whilethe Fourier representation only retains the frequency information, the wavelet representation contains both frequency and timeinformation. Since it is impossible to compute all of the wavelet coefficients, we will use the discrete wavelet transform to analyzeour signal.

The filter bank splits the image into various frequency bands. To create a level one 2D filter bank, make twocopies of the image matrix. Run a low pass filter on one copy and a high pass filter on the other copy. Next downsample each copy ofthe image matrix by removing all of the even columns. Then recombine the two downsampled copies so that the new matrix has thesame matrix dimensions as the original. As a result, one half of the new matrix has been low passed while the other half has beenhigh passed. Now that you have filtered the column vectors, you need to do the same thing for the row vectors. The resulting matrixshould have four sections: a low passed section that was low passed again (approximation matrix), a low passed section that was thenhigh passed (horizontal details), a high passed section that was then low passed (vertical details), and a high passed section thatwas high passed again (diagonal details). The section that looks most like the original image is the one that was low passed twice.However, it is still blurrier than the original because the high frequencies were removed from the image. To create multi-levelfilter banks, continue to high pass, low pass, and then downsample the section of the matrix that is always low passed. To create ablurred image, zero out all of the matrices except for the approximation matrix, then apply the IDWT for the Haar wavelet.

We have found that the image is sharpened if you use a level 1 filter bank and even more so with a level 2filter bank. However, there is visually no difference between sharpening with a level 2 filter bank and a level 3 filter bank.Also if the amount you sharpen by is too great, then the sharpened image will have halos. However, as opposed to diffuse halos thatare produced by sharpening with a Gaussian blur, the filter banks produce a somewhat blockier halo effect. While no information isgained by applying an unsharp mask, it can be used to enhance the images produced by some of our own images.