#Fixes gh_82 refined diagram of numpy benefits for black hole cs

Author: shaloo

content/en/case-studies/blackhole-image.md

@@ -59,4 +59,4 @@ The challenge posed during reconstruction of an image using VLBI measurements is
 
 NumPy enabled researchers to manipulate large numerical datasets through its efficient data structures of vectors and matrices leading to imaging and plotting of the first ever image of a black hole. Imaging of M87 black hole is a major scientific feat that was almost presumed impossible a century ago.  In a way, black hole image has helped in a stunning confirmation of Einstein’s general theory of relativity. This is not only a breakthrough in technology, but an example of international scale collaboration that uses connections between the world's best radio observatories, over 200 scientists worked with observations collected over 10 days and analyzed for over a year. They used innovative algorithms and data processing techniques improving upon existing astronomical models to help unfold some of the mysteries of the universe.
 
-{{< figure src="/images/content_images/cs/numpy_benefits.png" class="fig-center" alt="benefits" caption="**Key NumPy Capabilities utilized**" >}}
+{{< figure src="/images/content_images/cs/numpy_bh_benefits.png" class="fig-center" alt="benefits" caption="**Key NumPy Capabilities utilized**" >}}