The scale-invariant feature transform (SIFT) ability to automatic control points (CPs) extraction is very well known on remote sensing images, however, its result inaccurate and sometimes has incorrect matching from generating a small number of false CPs pairs, their matching has high false alarm. The RMSEs of the first-, second-, and third-order transformations range from 22.75 to 68.70, 17.9 to 52.15, and 12.00 to 29.25, respectively. The RMSE of the third polynomial transformation for misregistration is more accurate than that of the first-and second-order polynomial transformations. Verification is conducted by comparing the root mean square errors (RMSE) of these orders. The generated CPs are then applied to first-, second-, and third-order polynomials to calculate transformation coefficients and simulate different viewpoints. The proposed method is performed by generating tie points to automatically generate control points (CPs) from the image using Envi software. RazakSAT satellite image covering Kuala Lumpur-Pekan, Malaysia is investigated. This study presents a comparison of band-to-band registration of near-equatorial satellite image bands. Near-equatorial satellite image bands differ in viewing points, altitude, illumination, and satellite zenith, azimuth, and attitude. The results confirm the effectiveness of the proposedÄeveloping more accurate and efficient registration models for satellite images is important for remote sensing and GIS applications. Verification is performed byĬomparing the results of both automatic and manual transformations to the use of Those obtained with the use of spline transformation. Polynomial transformations are 4 and 3 m, respectively. Moreover, the root-mean-square errors of the first- and second-order Study are from the Malaysian RazakSAT satellite. To correct the misregistration between NEqO image bands. Registration with both first- and second-order polynomials and spline transformation Point (CP) generation through scale-invariant feature transform. Of image bands into greyscale, followed by image compression and automatic control The proposed method involves the conversion This study thus proposes a technique to overcome the band-toband Therefore band-to-band registration of a near-equatorial orbit The near-equatorial orbit (NEqO) image bands have large differences in distortion, Both automatic and manual evaluations confirm the effectiveness of the developed algorithms in multi-sensor data fusion for overall flat terrain without distinctive features. These algorithms are particularly useful to the image scenes where no distinctive features are available. In this paper, we present automatic algorithms to achieve this goal. So multi-band registration within a single frame and frame-to-frame mosaicking are necessary to obtain a co-registered multispectral image for the entire monitoring area before any commercial product can be generated to support practical decision-making. Contiguous frames are captured as the platform flies. In such a case, the cameras may have shifting and rotational misalignment, even after careful adjustment. To reduce the cost, a multispectral system can be assembled by using individual cameras onboard a small aerial platform, such as a miniature unmanned aerial vehicle (mini-UAV). The major obstacle in practical use is its high cost. Airborne remote sensing has important applications in agriculture monitoring because of the flexibility of system deployment.
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