Experimental Method
The compressibility used by this experiment is defined in the following equation.

Compressibility = {(Amount of Compressed Image Data) /(Amount of Original Image Data)} x 100 (%)           (3.1)

PSNR which shows signal-to-noise ratio is widely used as evaluated value of picture quality, and it is defined in the following equation.

It is the least square error in which the above equation gives MSE in (3.2). In equation (3.3), M X N is the image size. x₁(j,i) andare pixel value of original image and restoration image of band 1. Similarly, the sub script 2 ~ 7 shows each band. It is shown that the picture quality is better, as the value is higher for PSNR.

The experiment carried out the compression using vector quantization of the innerband pixel block and vector quantization of the interband identity position pixel block. The huffman code was applied for the data which showed the correspondence with the number of the codebook. As a comparison object, in predictive coding and reversible encoding by huffman code and irreversible encoding, the encoding by wavelet transform is used. In the encoding by wavelet transform, the thresholding of the subband did the frequency of the subband division on 2 times and 3 times, stepsize in the quantization on case from 1 to 8 and 0% ( the thresholding is not made ), 0.5%, 1% and 2% of the largest electric power value.

Experimental Result
In the vector quantization of the interband pixel block, the data to which the codebook shows the correspondence between 4096 byte and number of the codebook becomes for the 114,688 byte, and it becomes a total for the 118,784 byte. Therefore, it becomes 6.47% compressibility. It becomes the 94,908 byte, when the huffman code is done for the data which shows the correspondence with the number of the codebook, and it becomes in the whole with the 990,004 byte, and it becomes 5.40% compressibility. PSNR is 32.208027dB. In the vector quantization of the interband identity position pixel block, the file to which the codebook shows the correspondence between 1,792 byte and number of the codebook becomes the 263,936 byte, when it becomes the 262,144 byte totaled. Therefore, it becomes 14.38% compressibility. It becomes the 231,707 byte, when the huffman code is done for the data which shows the correspondence with the number of the codebook, and it becomes in the whole with the 233,499 byte, and it becomes 12.72% compressibility. PSNR is 36.998659dB. In the reversible encoding, the original picture size became, and 1,835,008 byte and compression size became 1,003,129 byte, 54.666% compressibility.

Summary
On the case of the vector quantization, the picture quality is clearly better than the case in which the wave let conversion was used, and the compressibility has improved in the condition that the compression for information of vector number and codebook is not carried out. It seems to obtain the better efficiency, if that it makes large number of images as an element and makes the codebook in the every type of the sensor is possible in respect of the codebook. In the vector quantization of the innerband pixel block, block strain which can be clearly confirmed in visual observation appears. And, it is proven that the high frequency component has been lost. It was able to be confirmed that the image in which it is considerably similar even in visual observation to original picture was obtained in the vector quantization of the interband identity position pixel block.

On the vector quantization, the preparation of the codebook seems to become an important problem. It is connected with earning considerable compressibility, if the common codebook is made. However, the codebook which made large number of images in the element is necessary. This time, it is necessary to choose the image for the codebook preparation in order to contain various regions and various seasons in order to consider and, the existence of seasons peculiar object, etc. so that the type of the object which has been projected in the image may increase. Concerning it, it seems to be effective for improving the picture quality to make small size codebook, when the common codebook was made.

Reference

• Makoto Miyahara : "systematic image coding", IPC Co., 1991.
• Takeshi Agui, Masayuki Nakajima : "image processing", Morikita publication, 1991.
• Inst. of Television Engineers of Japan : "the image information compression", ohm Co., 1991.