  ADITYA-L1 is India's first space mission to study the Sun from Lagrangian 1
position. { \textit{Visible Emission Line Coronagraph}} (VELC) is one of the
seven payloads in ADITYA-L1 mission scheduled to be launched around 2020. One
of the primary objectives of the VELC is to study the dynamics of coronal mass
ejections (CMEs) in the inner corona. This will be accomplished by taking high
resolution ($\approx$ 2.51 arcsec pixel$^{-1}$) images of corona from 1.05
R$_{\odot}$ -- 3 R$_{\odot}$ at high cadence of 1 s in 10 \AA\ passband
centered at 5000 \AA. Due to limited telemetry at Lagrangian 1 position we plan
to implement an onboard automated CME detection algorithm. The detection
algorithm is based on the intensity thresholding followed by the area
thresholding in successive difference images spatially re-binned to improve
signal to noise ratio. We present the results of the application of this
algorithm on the data from existing space- and ground-based coronagraph. Since,
no existing space-based coronagraph has FOV similar to VELC, we have created
synthetic coronal images for VELC FOV after including photon noise and injected
different type of CMEs. The performance of CME detection algorithm is tested on
these images. We found that for VELC images, the telemetry can be reduced by a
factor of 85\% or more keeping CME detection rate of 70\% or above at the same
time. Finally, we discuss the advantages and disadvantages of this algorithm.
The application of such onboard algorithm in future will enable us to take
higher resolution images with improved cadence from space and also reduce the
load on limited telemetry at the same time. This will help in better
understanding of CMEs by studying their characteristics with improved spatial
and temporal resolutions.
