This paper explores the use of an image sequence processing algorithm, called the simultaneous diagonalization (SD) filter, which can be effectively applied to long noisy image sequences. This filter was developed to filter a spatially invariant image sequence to form one new image in which a desired feature is enhanced and one or more undesired features (and noise) are suppressed in the filtered image. This filtering technique, applied to a long noisy image sequence, can be used to achieve significant data compression for image storage and provide surprisingly good enhanced image reconstructions. For this investigation, SD filtering is applied to a temporal image sequence, a renogram, with compression of a very noisy 180-image sequence to a 4-image set. The renogram, a nuclear medicine technique, was chosen due to its low signal-to-noise ratio over a long image sequence. Before the application of the SD filter, classical image processing techniques, median and averaging filtering, are used as a preliminary method to reduce the image sequence noise content. Compared to any of the images in the original image sequence, the reconstructed images are remarkably good. The SD filter with prefiltering, thus, can collect information distributed over a 180-image temporal sequence with low signal-to-noise ratio.