  Soft compression is a lossless image compression method, which is committed
to eliminating coding redundancy and spatial redundancy at the same time by
adopting locations and shapes of codebook to encode an image from the
perspective of information theory and statistical distribution. In this paper,
we propose a new concept, compressible indicator function with regard to image,
which gives a threshold about the average number of bits required to represent
a location and can be used for revealing the performance of soft compression.
We investigate and analyze soft compression for binary image, gray image and
multi-component image by using specific algorithms and compressible indicator
value. It is expected that the bandwidth and storage space needed when
transmitting and storing the same kind of images can be greatly reduced by
applying soft compression.
