
doi: 10.1109/csma.2015.53
In recent years, many approaches based on mathematical morphology have been applied in remote sensing image processing. In the paper, we proposed to use attribute profiles (APs) for textural extraction to the problem of content-based image retrieval (CBIR). In particular, four different attributes of APs with multiscale were applied to spatial information description. Then, the obtained textural images were processed by Gabor filters to generate the amplitude and energy coefficients. Finally, the extracted features along with histogram and color-moments were used for retrieval. The performance of textural descriptors were evaluated based on the UC Merced Land Use -- Land Cover data set. The experimental results show that the proposed method performs better than the popular Gabor texture.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
