The authors derive the multiple scattering expression within the framework of an IEM model for rough surface scattering. The complementary field coefficients are rederived based on a new surface slope expressions which are dependent on spatial variables. This leads to a more complete expression of the multiple scattering terms, thus allowing the authors to account for multiple effects more accurately. Numerical calculations and comparisons with numerical simulation are provided to demonstrate the results.

In this paper, a new repetition finder to be used with dynamic Huffman (1952) coding is proposed to improve the compression efficiency by reducing the redundancy due to string repetitions. Compared to the repetition finder proposed by Yokoo (1991), the proposed scheme effectively increases the numbers of consecutive symbols in the repetition mode and the total number of symbols in the repetition mode. Experimental results show that the proposed method outperforms the repetition finder of Yokoo by 14-40% in compression ratios with about the same memory requirement and running time.

A new automatic translation system between simplified and complex Chinese characters based on OCR approaches is proposed in this paper. This system can demonstrate an efficient feature extraction algorithm for recognizing either complex or simplified printed Chinese characters. In addition, a new post-processing model proposed in the authors' system not only translates texts between complex and simplified characters, but also corrects character recognition errors. Experimental results show that the average recognition rates are about 99.2% and 95.3% for single font and multi-font recognition respectively. In testing on real documents of simplified characters, it achieves a recognition rate of 96.2% without contextual post-processing. Using the proposed language model for post-processing, one can improve the final accuracy rate to 97.8% including the text translation process and the recognition error correction.

The problems arising in the modeling and coding of digital Chinese character patterns for noiseless compression purposes are discussed. The modeling is intended to capture the maximum redundancies of the source under the consideration of relevant parameters. In this study, a redundancy-gathering algorithm is proposed in which a 2-D parsing tree is used, and the nodes to extend the tree are ranked according to the maximum redundancy gathered. Hence, the modeling represented by the tree can achieve great performance in the small number of nodes. The algorithm is then applied to evaluate the performance of arithmetic coding for digital Chinese character patterns. The results are compared to those of the traditional compression methods. In the same complexity, the authors find that their algorithm can improve the coding efficiency as high as 25.54%, 30.23%, 32.17%, 15.90%, and 27.58%, for five Chinese fonts, respectively.