Image Processing in Python

If a blue value is less than 16, multiply it by 16 to scale it up to its proper value. Alternately if a blue value in the encoded image is 16 or more, it is random garbage and should be ignored (interpreted as 0). This should yield the recovered image, but all in the blue channel. As a final fix, the image should be in the red channel to look more correct, so change your code to also move the values from the blue channel to the red channel.

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explanation:

we can all learn from our past mistakes because we all have different ways of learning different types of techniques. my way may or may not another classmate remember and have the repetition to acknowledge such standard. such as remembering acronyms. using abbreviations to us remember keep things in order in our memory. this us figure out what comes next in the sequence. if so, what we have is a sentence of just letters all in caps. we either know the meaning or have no idea what it stands for. most of the time we know the meaning and context. but most of us who don't know, should learn by having a quick glance at what needs to be remembered. such as repetition in the memory for acronyms. one way that me, is the fact that i'm always doing math and english assignments. so we have to remember specific meanings such as soapstone for documents, such as citing correctly. or pemdas for doing the equations correctly, even if it's the super long way. this works for everyone. you just have to find what works for you by practicing and repetition daily.