Additionally, these can be changed dynamically during a simulation. The first set of experiments focuses on assessing the type of performance one may expect for various choices of integer and fractional bits in a fixed-point implementation of the compression algorithm. The image used in this study was a 128x128 version of the Lena image. The two surface plots shown below contain the results of the study. The number of integer bits was varied from 4 up to 24, and the number of fractional bits from 3 up to 16.
Some trends are immediately obvious from the data.
We see that for both integer and real-valued wavelets, increasing the number of integer bits up to 8 results in significant improvement in image quality, but increasing the integer bits beyond 8 results in little, if any, improvement. As one may expect, for integer wavelets, the number of fractional bits appears to have an effect on the performance of the algorithm. These trends are seen in the two surface plots shown in Figure 2 below. These images consist of a satellite image, a text image and a few natural images. The bit-rates considered were 0.25, 0.5, 0.75, 1.0 and 2.0 bits per pixel.