After Ranger 7, NASA moved on to Mars, deploying Mariner 4 in November 1964. It was the first probe to send signals back to Earth in digital form, which was necessitated by the fact that the signals had to travel 216 million km back to earth. The receiver on board could send and receive data via the low- and high-gain antennas at 8⅓ or 33⅓ bits-per-second. So at the low end, one pixel (8-bit) per second. All images were transmitted twice to insure no data were missing or corrupt. In 1965, JPL established the Image Processing Laboratory (IPL).
The next series of lunar probes, Surveyor, were also analog (due to construction being too advanced to make changes), providing some 87,000 images for processing by IPL. The Mariner images also contained noise artifacts that made them look as if they were printed on “herringbone tweed”. It was Thomas Rindfleisch of IPL who applied nonlinear algebra, creating a program called Despike – it performed a 2D Fourier transform to create a frequency spectrum with spikes representing the noise elements, which could then be isolated, removed and the data transformed back into an image.
Below is an example of this process applied to an image from Mariner 9 taken in 1971 (PIA02999), containing a herringbone type artifact (Figure 1). The image is processed using a Fast Fourier Transform (FFT – see examples FFT1, FFT2, FFT3) in ImageJ.
Applying a FFT to the original image, we obtain a power spectrum (PS), which shows differing components of the image. By enhancing the power spectrum (Figure 2) we are able to look for peaks pertaining to the feature of interest. In this case the vertical herringbone artifacts will appear as peaks in the horizontal dimension of the PS. Now in ImageJ these peaks can be removed from the power spectrum, (setting them to black), effectively filtering out those frequencies (Figure 3). By applying the Inverse FFT to the modified power spectrum, we obtain an image with the herringbone artifacts removed (Figure 1, right).
Research then moved to applying the image enhancement techniques developed at IPL to biomedical problems. Robert Selzer processed chest and skull x-rays resulting in improved visibility of blood vessels. It was the National Institutes of Health (NIH) that ended up funding ongoing work in biomedical image processing. Many fields were not using image processing because of the vast amounts of data involved. Limitations were not posed by algorithms, but rather hardware bottlenecks.