Well, that looks a lot like what people are used to seeing when
they mess with images using a computer. (In fact this is a higher
quality conversion than most programs, as I did it in floating point
and dithered the results back to 8 bits. Most programs use an 8-bit to
8-bit lookup table which necessarily means some color information is
lost, due to the pigeonhole principle). Most users then give up after
seeing this, and use more complicated color corrections such as
histograms or lookup curves to get what they want.
But what if the math is done in Linear Floating Point? In these
next examples the image was converted from sRGB to linear floating
point, multiplied by a constant, and then converted back to sRGB:
Okay, I hope you can see that the second example looks a lot more like
an increased exposure of the image. Yes nothing fancy is being done,
just really simple math! Even if it is not perfect, it is much closer,
and the user has a lot less work to do to get it perfect.