![](bg8.png)
training and test processes the proposed method takes
is less than SRC takes, but more than CRC, NRS and
JCR take. In Table 2, the more accurate a method is,
the more computation time is generally required. This
demonstrates that accuracy comes at the cost of
increasing computational efforts. It is time
consuming to separately find out the most similar
training images for each test image and the most
frequent training images for every class with two
sub-dictionaries. The process occupies most of the
running time of the proposed method.
5 CONCLUSION
In this paper, experimental results clearly show that
the proposed method obtains the best classification
performance. It means the idea of training
dictionaries at two steps is promising, and encourages
me further to explore the direction. From Figure 4(a),
there still are many disturbances (for example,
estimated construction coefficients in class 8, 17 and
19). Effective methods for extracting discriminative
information of different classes should be explored to
decrease and even eliminate these disturbances.
Besides, time consuming on sub-dictionaries is also a
problem. To find out a way to reduce computing time
is necessary. Parallel computing can be thought as an
ideal direction in the future work.
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