Chien-Fa Li’s research while affiliated with National Chung Cheng University and other places

In this paper, the code transformation algorithms between the fixed binary linear quadtree scheme (FBLQ)and the constant bit-length linear quadtree scheme(CBLQ) are proposed. There exists no code transformation algorithm between FBLQ and CBLQ. To solve this problem that when one receives a FBLQ or CBLQ code and does not have the corresponding decoding program, with our new code transformation algorithms at hand, she/he can transform the received code into CBLQ or FBLQ code that she/he can handle.The code transformation algorithms can also be used to reduce the load an image lays on the system by transforming it from a higher complexity code to a lower one.

Progressive image transmission (PIT) techniques are useful in Web applications. A user can get a rough preview of an image and decide if the entire detail of a picture needs to be transmitted, especially when the network bandwidth is restricted. In this paper, we propose a new progressive image transmission scheme for Chinese calligraphy. Because the colors used in Chinese calligraphy are very simple, we can apply the quadtree-structure to transmit the calligraphy progressively. The preliminary results show that transmitted bits can be saved in the first few rounds. The PSNR values in the first few rounds are much better than other PIT techniques.

In this paper, algorithms for transforming code between bintree and quadtree are proposed. The quadtree and bintree are two commonly used representations for image manipulations. However, there exists no algorithm for transforming code between bintree and quadtree. When one receives a DF-expression of a bintree or quadtree code and does not have the corresponding decoding program, she/he, with our new code transformation algorithms at hand, can transform the received code into a quadtree or bintree code that she/he can handle. After code transformation, the receiver can see whether the output code is smaller than the input code. From it, she/he can further decide which code is more economic in its memory space needed; therefore, she/he can store the code with smaller size for saving more memory space.