| Paper ID | D-3-2.5 |
| Paper Title |
FIXED-POINT ARITHMETIC OF L2-NORM APPROXIMATION FOR 2-TUPLE ARRAYS WITH ROTATED L1-NORM EVALUATION |
| Authors |
Yuya Kodama, Shogo Muramatsu, Hiroyoshi Yamada, Niigata University, Japan |
| Session |
D-3-2: Multimedia Analysis and Others |
| Time | Thursday, 10 December, 15:30 - 17:15 |
| Presentation Time: | Thursday, 10 December, 16:30 - 16:45 Check your Time Zone |
|
All times are in New Zealand Time (UTC +13) |
| Topic |
Image, Video, and Multimedia (IVM): |
| Abstract |
This paper proposes a high-precision fast approximation method for the l2-norm evaluation of 2-tuple arrays by means of a rotated l1-norm evaluation with fixed-point arithmetic. A considerable number of calculations for 2-tuple l2-norm are frequently required in several signal processing applications such as image restoration with isotropic total variation and complex l1-norm regularization. Typical embedded applications prefer parallel processing, constant scaling, and fixed-point arithmetic compared with serial processing, variable multiplication, and floating-point arithmetic. To achieve a hardware-friendly calculation, square and square root operations should be adequately approximated. However, several existing techniques are challenged with respect to approximations with all three preferable features. Thus, in this paper, a hardware-friendly approximation algorithm is proposed. The proposed method uses the fact that the upper bound of the surface of a first-order rotational cone traces a second-order cone, i.e., l2-cone, requests less variable multiplication, and can easily be implemented in parallel with fixed-point arithmetic. To verify the effectiveness of the proposed method, an image restoration performance and software/hardware co-design report are evaluated. |